*** THE SOLUTIONS

How We Can Lock the Political Corruption Revolving Door In California And Washington DC

The NY Times reported: “Ms. Feinstein and her husband sold $1.5 million to $6 million worth of stock in Allogene Therapeutics, a California-based biotech company, in transactions that took place on Jan. 31 and Feb. 18.” She did claim that she has “no involvement in her husband’s financial decisions” to avoid criticism. Do you really think that she has no idea about multi-million dollar deals that her husband is involved in?
 

– A Plan To Increase Public Integrity And End This Corruption:

These are the steps that the public must demand to strengthen public integrity by eliminating corrupt financial conflicts in Congress.

Congress must be ordered to eliminate both the appearance and the potential for financial conflicts of interest. Americans must be confident that actions taken by public officials are intended to serve the public, and not those officials. These actions counter-act the actions taken by Obama Administration staff and Department of Energy officials in illicit coordination
with U.S. Senators. In other words, we experienced all of the damages from each of the abuse-of-power issues listed below. These are the actions needed to resolve those issues:

– Ban individual stock ownership by Members of Congress, Cabinet Secretaries, senior congressional staff, federal judges, White House staff and other senior agency officials while in office. Prohibit all government officials from holding or trading stock where its value might be influenced by their agency, department, or actions.

– Apply conflict of interest laws to the President and Vice President through the Presidential Conflicts of Interest Act, which would require the President and the Vice President to place conflicted assets, including businesses, into a blind trust to be sold off

– Require senior Department of Energy government officials, employees, contractors and White House staff to divest from privately-owned assets that could present conflicts, including large companies like Tesla, Google, Facebook, Sony, Netflix, etc., and commercial real estate.

– Make it a felony to not respond to a filing by a citizen within 48 hours. Former White House and Energy Department staff use ‘stone-walling’ to intentionally delay responses for a decade, or more.

– Apply ethics rules to all government employees, including unpaid White House staff and advisors.

– Require most executive branch employees to recuse from all issues that might financially benefit themselves or a previous employer or client from the preceding 4 years

– Create conflict-free investment opportunities for federal officials with new investment accounts managed by the Federal Retirement Thrift Investment Board and conflict-free mutual funds.

– Close and lock the Revolving Door between industry and government and stop tech companies from buying influence in the government or profiting off of the public service of any official.

– Lifetime ban on lobbying by Presidents, Vice Presidents, Members of Congress, federal judges, and Cabinet Secretaries; and, multi-year bans on all other federal employees from lobbying their former office, department, House of Congress, or agency after they leave government service until the end of the Administration, but at least for 2 years ( and at least 6 years for corporate lobbyists)

– Limit the ability of companies to buy influence through former government officials

– Require income disclosures from former senior officials 4 years after federal employment.

– Prohibit companies from immediately hiring or paying any senior government official from an agency, department, or Congressional office recently lobbied by that company

– Prohibit the world’s largest companies, banks, and monopolies (measured by annual revenue or market capitalization) from hiring or paying any former senior government official for 4 years after they leave government service.

– Limit the ability of companies to buy influence through current government employees

– Prohibit current lobbyists from taking government jobs for 2 years after lobbying; 6 years for corporate lobbyists. Public, written waivers where such hiring is in the national interest are allowed for non-corporate lobbyists only.

– Prohibit corporate outlaws like Google, Tesla, Facebook, Linkedin, Netflix, Sony, etc., from working in government
by banning the hiring of top corporate leaders whose companies were caught breaking federal law in the last 6
years

– Prohibit contractor corruption by blocking federal contractor and licensee employees from working at the agency awarding the contract or license for 4 years

– Ban “Golden Parachutes” that provide corporate bonuses to executives for federal service.

– Publicly expose all influence-peddling in Washington.

– Strengthen and expand the federal definition of a “lobbyist” to include all individuals paid to influence government.

– Create a new “corporate lobbyist” definition to identify individuals paid to influence government on behalf of for-
profit entities and their front-groups.

– Radically expand disclosure of lobbyist activities and influence campaigns by requiring all lobbyists to disclose any
specific bills, policies, and government actions they attempt to influence; any meetings with public officials; and any documents they provide to those officials

– End Influence-Peddling by Foreign Actors such as that which occurred in the ENER1, Severstal, Solyndra and related scandals

– Combat foreign influence in Washington by banning all foreign lobbying.

– End foreign lobbying by Americans by banning American lobbyists from accepting money from foreign governments, foreign individuals, and foreign  companies to influence United States public policy.

– Prohibit current lobbyists from taking government jobs for 2 years after lobbying; 6 years for corporate lobbyists. Public, written waivers where such hiring is in the national interest are allowed for non-corporate lobbyists only.

– End Legalized Lobbyist Bribery and stop lobbyists from trading money for government favors.

– Ban direct political donations from lobbyists to candidates or Members of Congress.

– End lobbyist contingency fees that allow lobbyists to be paid for a guaranteed policy outcome.

– End lobbyist gifts to the executive and legislative branch officials they lobby

– Strengthen Congressional independence from lobbyists and end Washington’s dependence on
lobbyists for “expertise” and information.

– Make congressional service sustainable by transitioning Congressional staff to competitive salaries that track other
federal employees

– Reinstate the nonpartisan Congressional Office of Technology Assessment to provide critical scientific and technological support to Members of Congress.

– Level the playing field between corporate lobbyists and government by taxing excessive lobbying beginning at $500,000 in annual lobbying expenditures, and use the proceeds to help finance Congressional mandated rule-making, fund the National Public Advocate, and finance Congressional support agencies

– De-politicize the rulemaking process and increase transparency of industry efforts to influence federal agencies.

– Require individuals and corporations to disclose funding or editorial conflicts of interest in research submitted to agencies that is not publicly available in peer-reviewed publications.

– Prevent McKinsey-type sham research from undermining the public interest by requiring that studies that present conflicts of interest to undergo independent peer review to be considered in the rule-making process

– Require agencies to justify withdrawn public interest rules via public, written explanations.

– Close loopholes exploited by powerful corporations like Google, Facebook, Tesla, Netflix, Sony, etc., to block public interest actions.

– Eliminate loopholes that allow corporations, like Tesla and Google, to tilt the rules in their favor and against the public interest.

– Restrict negotiated rule-making to stop industry from delaying or dominating the rule-making process by ending the practice of inviting industry to negotiate rules they have to follow.

– Restrict inter-agency review as a tool for corporate abuse by  banning informal review, establishing a maximum 45-
day review period, and blocking closed -door industry lobbying at the White House’s Office of Information and Regulatory Affairs

– Limit abusive injunctions from rogue judges, like Jackson, et al, by ensuring that only Appeals Courts, not individual District Court judges , can temporarily block agencies from implementing final rules.

– Prevent hostile agencies from sham delays of implementation and enforcement by using the presence of litigation to postpone  the implementation of final rules.

– Empower the public to police agencies for corporate capture.

– Increase the ability of the public to make sure their interests are considered when agencies act

– Create a new Office of the Public Advocate  empowered to assist the public in meaningfully engaging in the rule-making process across the federal government

– Encourage enforcement by allowing private lawsuits from members of the public to hold agencies accountable for failing to complete rules or enforce the law, and to hold corporations accountable for breaking the rules

– Inoculate government agencies against corporate capture such as Google undertook against the White House

– Provide agencies with the tools and resources to implement strong rules that reflect the will of Congress and protect the public.

– Boost agency resources to level the playing field between corporate lobbyists and federal agencies by using the proceeds of the tax on excessive lobbying and the anti-corruption penalty fees to help finance Congress-mandated rule-making and facilitate decisions by agencies that are buried in an avalanche of lobbyist activity

– Reform judicial review to prevent corporations from gaming the courts by requiring courts to presumptively defer to agency interpretations of laws and prohibiting courts from considering sham McKinsey studies and research excluded by agencies from the rule-making process

– Reverse the Congressional Review Act provision banning related rules that prevent agencies from implementing the will of Congress based on Congress’ prior disapproval of a different, narrow rule on a similar topic

– Improve judicial integrity and defend access to justice for all Americans.

– Strengthen Judicial Ethics Requirements.

– Enhance the integrity of the judicial branch by strengthening rules that prevent conflicts of interest.

– Ban individual stock ownership by federal judges.

– Expand rules prohibiting judges from accepting gifts or payments to attend private seminars from private individuals and corporations

– Require ethical behavior by the Supreme Court by directing the Court to follow the Code of Conduct that binds all other federal judges

– Boost the transparency of Federal Courts

– Enhance public insight into the judicial process by increasing information about the process and reducing barriers to accessing information.

– Increase disclosure of non-judicial activity by federal judges by requiring the Judicial Conference to publicly post judges’ financial reports, recusal decisions, and speeches.

– Enhance public access to court activity by mandating that federal appellate courts live-stream, on the web, audio of their proceedings, making case information easily-accessible to the public free of charge, and requiring federal courts to share case assignment data in bulk.

– Eliminate barriers that restrict access to justice to all but the wealthiest individuals and companies.

– Reduce barriers that prevent individuals from having their case heard in court by restoring pleading standards that make it easier for individuals and businesses that have been harmed to make their case before a judge.

– Encourage diversity on the Federal Bench

– Strengthen the integrity of the judicial branch by increasing the focus on personal and professional diversity of the federal bench.

– Create a single, new, and independent agency dedicated to enforcing federal ethics and anti-corruption laws

– Support stronger ethics and public integrity laws with stronger enforcement.

– Establish the new, independent U.S. Office of Public Integrity, which will strengthen federal ethics enforcement
with new investigative and disciplinary powers

– Investigate potential violations by any individual or entity, including individuals and companies with new subpoena authority

– Enforce the nation’s ethics laws by ordering corrective action, levying civil and administrative penalties, and referring egregious violations to the Justice Department for criminal arrest and enforcement.

– Receive and investigate ethics complaints from members of the public.

– Absorb the U.S. Office of Government Ethics as a new Government Ethics Division tasked with providing confidential advice to federal employees seeking ethics guidance.

– Consolidate anti-corruption and public integrity oversight over federal officials, including oversight of all agency Inspectors General, all ethics matters for White House staff and agency heads, and all waivers and recusals by senior government officials.

– Remain independent and protected from partisan politics through a single Director operating under strict selection, appointment, and removal criteria.

– Provide easy online access to key government ethics and transparency documents, including financial disclosures; lobbyist registrations; lobbyist disclosures of meetings and materials; and all ethics records, recusals, and waivers.

– Maintain a new government-wide Office of the Public Advocate, which would advocate for the public interest in executive branch rule-making.

– Enforce federal open records and FOIA requirements by maintaining the central FOIA website and working with the National Archives to require agencies to comply with FOIA.

– Strengthen legislative branch enforcement.

– Expand an independent and empowered ethics office insulated from congressional politics.

– Expand and empower the U.S. Office of Congressional Ethics, which will enforce the nation’s ethics laws in the Congress
and the entire Legislative Branch, including the U.S. Senate.

– Conduct investigations of potential violations of ethics laws and rules by Members of Congress and staff with new subpoena power

– Refer criminal and civil violations to the Justice Department, the Office of Public Integrity, or other relevant state or federal law enforcement.

– Recommend disciplinary and corrective action to the House and Senate Ethics Committees.

– Boost transparency in government and fix Federal Open Records laws, public official and candidate tax disclosure.

– Disclose basic tax return information for candidates for federal elected office and current elected officials.

– Require the IRS to release tax returns for Presidential and Vice-Presidential candidates from the previous 8 years and during each year in federal elected office.

– Require the IRS to release t ax returns for Congressional candidates from the previous 2 years and during each year in federal elected office.

– Require the IRS to release tax returns and other financial information of businesses owned by senior federal officials and
candidates for federal office

– Require the IRS to release tax filings for nonprofit organizations run by candidates for federal office

– Disclose the Cash behind Washington Advocacy and Lobbying.

– Prevent special interests from using secret donations from corporations and billionaires to influence public policy
without disclosure

– Require nonprofit organizations to list donors who bankrolled the production of any specific rule-making comment, congressional testimony, or lobbying material, and to reveal whether the donors reviewed or edited the document.

– Require individuals and corporations to disclose funding or editorial conflicts of interest in research submitted to agencies that is not publicly available in peer-reviewed publications.

– Prevent sham research from undermining the public interest by requiring that studies that present conflicts of interest to independent peer review to be considered in the rule-making process.

– Improve the Freedom of Information Act (FOIA)

– Close the loopholes in our open records laws that allow federal officials to hide tech industry and Silicon Valley oligarch industry influence

– Codify the default presumption of disclosure and affirmatively disclose records of public interest, including meeting agendas; government contracts; salaries; staff diversity; and reports to Congress.

– Require all agencies to use a central FOIA website that is searchable and has downloadable open records databases with
all open FOIA requests and all records disclosed through FOIA.

– Strengthen FOIA enforcement by limiting FOIA exemptions and loopholes, and by giving the National Archives the authority to overrule agency FOIA decisions and to compel disclosure.

– Extend FOIA to private-sector federal contractors, including private federal prisons and immigration detention centers, and require large federal contractors to disclose political spending

– Make Congress more transparent by ending the corporate lobbyists leg up in the legislative process. The
public deserves to know what Congress is up to and how lobbyists influence legislation.

– Require all congressional committees to immediately post online more information, including hearings and markup schedules, bill or amendments text, testimonies, documents entered into the hearing record, hearing transcripts, written witness answers, and hearing audio and video recordings.

– Require Members of Congress to post a link to their searchable voting record on their official websites

– Require lobbyists to disclose when they lobby a specific congressional office; specific topics of visit; the official action being requested; and all documents provided to the office during the visit.

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Do these seem like common-sense rules that should have already been in place? They are!

These anti-corruption rules have been blocked by your own elected officials because they work for themselves and not you!

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A group of domestic citizens filed FBI complaints and lawsuits against White House and government agency senior staff and their Silicon Valley oligarch financiers including a lawsuit against a rogue, dirty tricks, off-shoot of the CIA called “In-Q-Tel”.

These citizens instigated Congressional corruption investigations and hearings against the most senior members of the State and Federal government. These actions resulted in the termination of very famous public officials including the Secretary of Energy, his staff, White House Executives and more. The case broke-up some of their crony criminal embezzlement scams. It nearly resulted in the President being forced to leave office, mid-term, based on revelations of a massive crony stock market kick-back scheme which began to be exposed after the FBI raid of Solyndra. The director of the FBI was fired for assisting in cover-ups related to this matter because the matter was reported directly to him.

This natural-born, American, domestic group of engineers was attacked with a $30 million dollar+ (per uncovered billing notices) retribution/political reprisal program contracted by White House political operatives, and their appointees, who were also the business competitors of the engineers.

The attackers used Fusion GPS-type character assassination smear campaigns (operated by their cronies at Google, Gawker, Gizmodo, Jalopnik and Facebook), NVCA black-listing, Solyndra-laundering, stone-walling, Lois Lerner-class agency manipulation and search engine rigging. In-Q-Tel turns out to be the only federally financed “charity” whose staff are also employed by each of the suspects in this case and who financed the suspects in this case. It was revealed that White House executives ordered government agencies to harm members of the public and to reprisal with-hold public resources from the public. This was a violation of tort, RICO and anti-trust laws.

The citizens had previously been awarded federal commendations, state and federal innovation grants, government R&D contracts and knew White House and Congressional executives personally. They know “where the bodies are buried”.

The citizen-victims fought back.

With the encouragement of members of Congress they used 100% legal tools to interdict the corruption.

Essentially; they helped the United States government sue itself!

First, with a unique new kind of pioneering federal lawsuit, victims established — FOR THE FIRST TIME IN LEGAL HISTORY — that political cronyism is a valid basis for a claim of arbitrary-and-capricious agency action under the Administrative Procedure Act. See: Federal Case One, (D.D.C. 2015).

Second, they prevailed in the United States Court of Appeals for the District of Columbia Circuit on their appeal of the district court’s ruling that an agency may escape judicial review of its action by requesting a voluntary remand but refusing to reconsider its initial denial of an application. See: Case Federal Two, (D.C. Cir. 2017). The Washington DC Circuit agreed with the victims that an agency may only seek a remand if it promises to reconsider its initial decision. It is because of that victory that the government, under court order is now re-doing the victims applications and GAO, FBI, IG’s and Congressional oversight offices are watching to assure effective ethics and transparency.

Third, these cases placed, on permanent public record, one of the most detailed documentation sets, ever assembled, about how modern political “Dark Money” conduits operate. The legal team hired ex-FBI, CIA and SEC experts to track down covert bank accounts, revolving door bribes, insider stock trades and other payola between the victim’s competitors and public officials. This documentation now prevents the use of those kinds of criminal efforts, in the future, by exposing their tactics to the public.

Fourth, the victim’s team engaged in the interdiction and termination of corrupt agency executives, contractors and their financiers. This included some of the most well-known names in Washington, DC, at the time. Many of them were, and are still being, investigated and surveilled by the FBI, GAO, SEC and Congress.

Fifth, and most important, the effort put every corrupt political scheme on notice that they WILL be found out and interdicted!

The bottom line?

The victims group WON on every single aspect of their public-interest goals but still have yet to be recompensed for their damages! They continue to fight for their Constitutional rights and the payment of their damages and benefits fro the government.

They have won over and over while the opposition keeps getting fired, arrested, investigated and exposed in national news documentaries!

Now the “bad guys” have less options to engage in the corruption of our Democracy!

You’re Welcome, America!

These co-workers witnessed politicians and Silicon Valley oligarchs (sometimes called “The Deep State”) stealing money from both: 1.) Their company and 2.) the US Government Treasury and handing it to Elon Musk and their other insider friends. They reported it to the authorities.

The crime turned out to be part of one of the biggest embezzlement crimes ever exposed. Major political figures and tech “bosses” turned out to be running a “PayPal Tech Mafia”. The bad guys then began hunting them down and attacking them in reprisal “for the rest of our lives” per their threats and their ongoing retribution vendettas.

It was found that famous senators, their Silicon Valley oligarch financiers and their associates run an organized crime insider trading scam that abuses taxpayers and sabotages competing businesses. The terminations of the heads of the FBI, The Department of Energy and other famous people in politics is because of their operation, and cover-ups, of this case. The cover-ups are still going on. The Wenstein, Epstein and related cases show, though, that cover-ups never last.

Now, over 300 million potential voters can “crowd-source” join the forensic efforts to expose, shame, dox, bankrupt, boycott and 100% legally exterminate the corrupt entities who did these illicit things by using our Democracy as their billionaire’s plaything.

Hundreds of the perpetrators have already been fired, placed under permanent public surveillance, financially tracked through every asset, reported to federal agencies and targeted for investigation. The goal is to interdict every single person, company and political operative group who is engaging in these crimes using crowd-sourced investigation and intelligence tools.

This is a large part of all of that “political corruption” and “dirty Dark Money” politics you read about in the newspaper every day.

If you thought that Mossack Fonseca and the Panama Papers was “The Story”: IT WAS ONLY THE BEGINNING!

A key part of one of the testimony statements reads: “…SILICON VALLEY’S POLITICIANS MAKE POLICY THAT, BOTH, RUINS TAXPAYERS WHILE MAKING THE POLITICIANS RICH BY ARTIFICIALLY INFLATING THE VALUE OF THE POLITICIANS SECRET STOCK MARKET HOLDINGS. NOW WE ARE EXPOSING THEIR ENTIRE SCAM!

THIS IS ABOUT THE U.S. SENATORS AND THEIR CRONY DARK MONEY POLITICAL BRIBES AND CRIMINAL KICK-BACKS, THE TECH OLIGARCHS WHO DEPLOYED THE BRIBES AND THE VICTIMS OF THESE CRIMES.

IMAGINE LIVING IN A WORLD WHERE ALMOST EVERY ONE OF THE PUBLIC OFFICIALS THAT WERE SUPPOSED TO HELP YOU TURNED OUT TO BE YOUR BUSINESS COMPETITORS. IMAGINE HAVING THEM USE GOVERNMENT RESOURCES TO PROFIT AT YOUR EXPENSE, BLOCKADE YOU AND TREAT DEMOCRACY LIKE A GARAGE SALE! THIS IS THAT STORY!…”

Google, Tesla, Facebook, Linkedin and their VC’s (and deeply bribed Senators) operated hit-jobs on the public and their competitors, supported by the Obama White House and U.S. Dept. of Energy.

This is about a group of tech oligarchs, and their corrupt Senators, who commit crimes in order to manipulate over a trillion tax dollars (YOUR MONEY) into their, and their friends pockets.

They are felons yet they control some of the offices of the agencies who are supposed to arrest them. Silicon Valley bought K Street and U.S. Senators, gave them more Dark Money than history has ever seen and then had giant tech-law firms bribe, hit-job and blockade any attempts to solve the problem.

Some of the largest bribes in American history were paid via billions of dollars of pre-IPO cleantech stock, insider trading, real estate, Google search engine rigging and shadow-banning, sex workers, revolving door jobs, nepotism, state-supported black-listing of competitors and under-the-table cash. Why are these Silicon Valley Oligarchs and their K-Street law firms and lobbyists immune from the law?

U.S. Senators, Agency Heads and Congress were bribed with:

– Billions of dollars of Google, Twitter, Facebook, Tesla, Netflix and Sony Pictures stock and stock warrants which is never reported to the FEC

– Billions of dollars of Google, Twitter, Facebook, Tesla, Netflix and Sony Pictures search engine rigging including shadow-banning, de-boosting, DNS re-routing, directed search suggestion, subliminal messaging bias, and hundreds of other psychological manipulation tricks; the value of which is never reported to the FEC but proven by invoices and bank payments between Google and Gawker, Gizmodo, DNC, Fusion GPS, Black Cube, etc.

– Free rent

– Prostitutes and Rent Boys

– Cars

– Dinners

– Party Financing

– Sports Event Tickets

– Campaign Services “Donations”

– Secret PAC Financing

– Jobs in Corporations in Silicon Valley For The Family Members of Those Who Take Bribes And Those Who Take Bribes, Themselves

– “Consulting” contracts from McKinsey as fronted pay-off gigs

– Overpriced “Speaking Engagements” which are really just pay-offs conduited for donors

– Private jet rides and use of Government fuel depots (ie: Google handed out NASA jet fuel to staff)

– Real Estate

– The use of Cayman, Boca Des Tores, Swiss and related laundering accounts

– The use of HSBC, Wells Fargo and Deustche Bank money laundering accounts

– Free spam and bulk mailing services owned by corporations

– Use of high tech law firms such as Perkins Coie, Wilson Sonsini, MoFo, Covington & Burling, etc. to conduit bribes to officials

Investigators were able to get a law produced that made insider trading less attractive for Congress, nothing has been done to stop stock warrant bribes and revolving door payola. Additionally, even with the new law, 60% of the U.S. Congress (including their associates and families) STILL engage in insider trading because law enforcement has not prosecuted many of them.

This is about a group of U.S. Senators, Silicon Valley Oligarchs, Crooked Law Firms and Lobbyists who commit crimes in order to manipulate over a trillion tax dollars into their, and their friends pockets. They use media monopoly tricks to try to shut out any other viewpoints. They push pretend issues that they believe will get more tax money allocated to “issue solutions” that they, and their friends, happen to already own the monopolies for. They are felons yet they control some of the offices of the agencies who are supposed to arrest them. Silicon Valley bought K Street lobby firms and U.S. Senators, gave them more Dark Money than history has ever seen and then had giant tech-law firms bribe, hit-job and blockade any attempts to arrest them.

Said one victim: “They had the U.S. Government hire us, paid us part of our money, then asked us to spend our life savings and years of our time on their federal project based on their lies and false-promises. Then they took the assets we were asked to invest, plus the money they owed us, and gave it to their friends. When we complained to the FBI, Congress and the SEC, they hired Fusion GPS-like companies to run “hit-jobs” on us and threaten our lives. WE WERE LIED TO AND DEFRAUDED BY GOVERNMENT AGENCIES. THEY TOOK OUR MONEY AND USED US, AND OUR PEERS, AS A SMOKE-SCREEN TO HIDE THEIR CRONY PAYOLA CRIME THAT PUT TAXPAYER CASH IN THEIR FRIEND’S POCKETS…We have received ZERO justice and ZERO compensation for our damages!”

There are no “conspiracy theories” here. These are all hard forensic facts that will stand-up in any court!

“…They did this to anybody who they thought might expose the White House use of agencies as “slush-funds” and “Dark Money” campaign finance laundering conduits. They were afraid that exposure of these schemes would cause the President of the United States to be forced to resign in the middle of his term!…”

Years of archived news videos provide evidence, by thousands of reporters and investigators, that the suspects are: A.) Based around Silicon Valley and Washington DC; B.) Operating as a RICO-violating cartel; C.) Deeply sociopath and sexually disturbed; D.) Money laundering via large law firms and investment banks; E.) Using Google, Reddit, Facebook, etc. as mass political behavior-manipulation programs; F.) Paying for and operating character assassination programs against those who defy them; G.) Using “green energy” as one of their facades to steer tax dollars to the companies that they, and their friends, already own and work for; H.) Willing to resort to the most extreme things to protect their scheme; I). Living in an ideological “echo-chamber” in their tech bubbles; J.) Empowered entirely by the public’s lack of willingness to boycott them and demand their arrests.

A vast number of individuals and companies, who are willing to testify about these crimes have NEVER BEEN ALLOWED into a Congressional hearing, court-room, FBI 302 interview reports, etc., because crooked Senators are terrified of the confirming testimony they can all provide.

Investigators placed autonomous monitoring applications on a vast number of co-location servers, shared hosting ISPs, stand-alone servers and sites around the world over ten years ago and monitored: 1.) Google search results compared to other search engines, 2.) Google DNS and spoofing activities, 3.) Google results on 100 key search terms including search terms of assets, candidates and business associates connected to Google, 4.) Where Google sends data from users clicking on Google supplied links, 5.) Where fabricated mole data that was injected as user data ultimately ended up later, and other metrics. The results prove that Google abuses the market, the public, politics and human rights.

Said another witness: “…ELON MUSK BOYFRIENDS: LARRY PAGE, ERIC SCHMIDT, JARED COHEN AND SERGY BRIN AT GOOGLE AND MARK ZUCKERBERG AT FACEBOOK ORDER THEIR COMPANY STAFF TO HIDE, DOWN-RANK, HOLE-PUNCH THE NET, SHADOW-BAN, STOCK MARKET VALUATION MANIPULATE AND EXCLUDE THIS WEBSITE ON THE INTERNET. WE TRACK EVERY TECHNICAL TRICK THEY USE AND REPORT IT TO CONGRESS AND ANTI-TRUST AGENCIES. THE MORE THEY DO IT, THE MORE THEY CREATE EVIDENCE THAT WILL PUT THEM OUT OF BUSINESS!…”

The Google empire controls most of the media on Earth, via many front corporations, and indoctrinates everyone in it’s organization using ‘cult’ methodologies. Google owner’s believe in “our-ideology-at-any-cost” and “the-ends-justify-the-means” scenarios. What could possibly go wrong?

Regarding The CleanTech Crash: Every single Dept of Energy executive, and related Senator, owns stock market assets in Tesla, Fisker, Solyndra, Ener1, etc. so they blockaded and sabotaged every applicant who competed with their holdings in a RICO-violating, felony organized crime, using taxpayer funds.

Many of those character assassinated, sabotaged, black-listed, poisoned and shadow-banned are still waiting for justice!

The Silicon Valley Mafia is The Sandhill Road Venture Capital frat boy company bosses in Palo Alto, their National Venture Capital Association (NVCA) partners and the tech companies (Google, Tesla, Facebook, Amazon, Twitter, Linkedin, etc.) they control. They are sometimes referred to as The Deep State. They have purchased California, New York and Washington, DC politicians (mostly Senators) who they also control.

They hire rogue ex-intelligence agents to operate attacks via Fusion GPS, The Gawker/Gizmodo/Jalopnik/Univision Hatchet-Job Fake Tabloid Facade (ie: Obama had White House staff: Robert Gibbs and John Podesta hire them, in association with Obama financier Elon Musk, to attack XP Vehicles, Bright Automotive and ZAP Vehicles as retribution in violation of anti-trust laws), Black Cube, ShareBlue, New America, In-Q-Tel, Podesta Group, Media Matters, etc. . They spend over $30M on each massive media attack program against competitors, reporters and outsiders.

They collude on black-lists, valuation controls, election manipulation, search engine rigging, domestic spying for political manipulation, stock rigging, insider trading, executive prostitute clubs, trophy wife assignments, the bribery of politicians and worse. They are felons who pay politicians to halt investigations and interdiction efforts. They are widely covered in news media articles as: sex abusers, cult enthusiasts, elitists, rapists, woman beaters, sexual work extortion operators, extremists, arrogant clones of each other, tone deaf, echo-chamber reinforcing, misogynist, racist, manipulative, insecure, covertly gay, corrupt, thieves’ and other anti-social revelations.

The divorce and sex abuse court filings against the #PaloAltoMafia men of Silicon Valley are some of the most disturbing and sexually twisted court records you will ever read and they demonstrate a clear and decades-long pattern of collusion and depravity. From Google’s “Sex Slaves” to “Sex Penthouses” to “Deaths by Prostitute”; the list is endless.

They are not limited to California and also operate out of New York and Washington DC. They use their monopolistic control of the internet to massively and exclusively scale services that only they control and use to abuse public privacy, human rights, invention rights and information. They run their cartel like the old Italian Mafia once did.

Silicon Valley’s Corrupt Palo Alto Mafia Network “Scaled Monopolies”

Dr. ROBERT EPSTEIN describes how Defendant and political financier Google (In-Q-Tel’s business partner) rigs elections to try to maintain Google’s monopoly.

Authorities in the UK have finally figured out that fake news stories and Russian-placed ads are not the real problem. The UK Parliament is about to impose stiff penalties—not on the people who place the ads or write the stories, but on the Big Tech platforms that determine which ads and stories people actually see.

Parliament’s plans will almost surely be energized by the latest leak of damning material from inside Google’s fortress of secrecy: The Wall Street Journal recently reported on emails exchanged among Google employees in January 2017 in which they strategized about how to alter Google search results and other “ephemeral experiences” to counter President Donald Trump’s newly imposed travel ban. The company claims that none of these plans was ever implemented, but who knows?

While U.S. authorities have merely held hearings, EU authorities have taken dramatic steps in recent years to limit the powers of Big Tech, most recently with a comprehensive law that protects user privacy—the General Data Protection Regulation—and a whopping $5.1 billion fine against Google for monopolistic practices in the mobile device market. Last year, the European Union also levied a $2.7 billion fine against Google for filtering and ordering search results in a way that favored their own products and services. That filtering and ordering, it turns out, is of crucial importance.

As years of research I’ve been conducting on online influence has shown, content per se is not the real threat these days; what really matters is (a) which content is selected for users to see, and (b) the way that content is ordered in search results, search suggestions, news feeds, message feeds, comment lists, and so on. That’s where the power lies to shift opinions, purchases, and votes, and that power is held by a disturbingly small group of people.

I say “these days” because the explosive growth of a handful of massive platforms on the internet—the largest, by far, being Google and the next largest being Facebook—has changed everything. Millions of people and organizations are constantly trying to get their content in front of our eyes, but for more than 2.5 billion people around the world—soon to be more than 4 billion—the responsibility for what algorithms do should always lie with the people who wrote the algorithms and the companies that deployed them.

In randomized, controlled, peer-reviewed research I’ve conducted with thousands of people, I’ve shown repeatedly that when people are undecided, I can shift their opinions on just about any topic just by changing how I filter and order the information I show them. I’ve also shown that when, in multiple searches, I show people more and more information that favors one candidate, I can shift opinions even farther. Even more disturbing, I can do these things in ways that are completely invisible to people and in ways that don’t leave paper trails for authorities to trace.

Worse still, these new forms of influence often rely on ephemeral content—information that is generated on the fly by an algorithm and then disappears forever, which means that it would be difficult, if not impossible, for authorities to reconstruct. If, on Election Day this coming November, Mark Zuckerberg decides to broadcast go-out-and-vote reminders mainly to members of one political party, how would we be able to detect such a manipulation? If we can’t detect it, how would we be able to reduce its impact? And how, days or weeks later, would we be able to turn back the clock to see what happened?

Of course, companies like Google and Facebook emphatically reject the idea that their search and newsfeed algorithms are being tweaked in ways that could meddle in elections. Doing so would undermine the public’s trust in their companies, spokespeople have said. They insist that their algorithms are complicated, constantly changing, and subject to the “organic” activity of users.

This is, of course, sheer nonsense. Google can adjust its algorithms to favor any candidate it chooses no matter what the activity of users might be, just as easily as I do in my experiments. As legal scholar Frank Pasquale noted in his recent book “The Black Box Society,” blaming algorithms just doesn’t cut it; the responsibility for what an algorithm does should always lie with the people who wrote the algorithm and the companies that deployed the algorithm. Alan Murray, president of Fortune, recently framed the issue this way: “Rule one in the Age of AI: Humans remain accountable for decisions, even when made by machines.”

Given that 95 percent of donations from Silicon Valley generally go to Democrats, it’s hard to imagine that the algorithms of companies like Facebook and Google don’t favor their favorite candidates. A newly leaked video of a 2016 meeting at Google shows without doubt that high-ranking Google executives share a strong political preference, which could easily be expressed in algorithms. The favoritism might be deliberately programmed or occur simply because of unconscious bias. Either way, votes and opinions shift.

It’s also hard to imagine how, in any election in the world, with or without intention on the part of company employees, Google search results would fail to tilt toward one candidate. Google’s search algorithm certainly has no equal-time rule built into it; we wouldn’t want it to! We want it to tell us what’s best, and the algorithm will indeed always favor one dog food over another, one music service over another, and one political candidate over another. When the latter happens … votes and opinions shift.

Here are 10 ways—seven of which I am actively studying and quantifying—that Big Tech companies could use to shift millions of votes this coming November with no one the wiser. Let’s hope, of course, that these methods are not being used and will never be used, but let’s be realistic too; there’s generally no limit to what people will do when money and power are on the line.

1. Search Engine Manipulation Effect (SEME)
Ongoing research I began in January 2013 has shown repeatedly that when one candidate is favored over another in search results, voting preferences among undecided voters shift dramatically—by 20 percent or more overall, and by up to 80 percent in some demographic groups. This is partly because people place inordinate trust in algorithmically generated output, thinking, mistakenly, that algorithms are inherently objective and impartial.

But my research also suggests that we are conditioned to believe in high-ranking search results in much the same way that rats are conditioned to press levers in Skinner boxes. Because most searches are for simple facts (“When was Donald Trump born?”), and because correct answers to simple questions inevitably turn up in the first position, we are taught, day after day, that the higher a search result appears in the list, the more true it must be. When we finally search for information to help us make a tough decision (“Who’s better for the economy, Trump or Clinton?”), we tend to believe the information on the web pages to which high-ranking search results link.

As The Washington Post reported last year, in 2016, I led a team that developed a system for monitoring the election-related search results Google, Bing, and Yahoo were showing users in the months leading up to the presidential election, and I found pro-Clinton bias in all 10 search positions on the first page of Google’s search results. Google responded, as usual, that it has “never re-ranked search results on any topic (including elections) to manipulate political sentiment”—but I never claimed it did. I found what I found, namely that Google’s search results favored Hillary Clinton; “re-ranking”—an obtuse term Google seems to have invented to confuse people—is irrelevant.

Because (a) many elections are very close, (b) 90 percent of online searches in most countries are conducted on just one search engine (Google), and (c) internet penetration is high in most countries these days—higher in many countries than it is in the United States—it is possible that the outcomes ofupwards of 25 percent of the world’s national elections are now being determined by Google’s search algorithm, even without deliberate manipulation on the part of company employees. Because, as I noted earlier, Google’s search algorithm is not constrained by equal-time rules, it almost certainly ends up favoring one candidate over another in most political races, and that shifts opinions and votes.

2. Search Suggestion Effect (SSE)
When Google first introduced autocomplete search suggestions—those short lists you see when you start to type an item into the Google search bar—it was supposedly meant to save you some time. Whatever the original rationale, those suggestions soon turned into a powerful means of manipulation that Google appears to use aggressively.

My recent research suggests that (a) Google starts to manipulate your opinions from the very first character you type, and (b) by fiddling with the suggestions it shows you, Google can turn a 50–50 split among undecided voters into a 90–10 split with no one knowing. I call this manipulation the Search Suggestion Effect (SSE), and it is one of the most powerful behavioral manipulations I have ever seen in my nearly 40 years as a behavioral scientist.

How will you know whether Google is messing with your election-related search suggestions in the weeks leading up to the election? You won’t.

3. The Targeted Messaging Effect (TME)
If, on Nov. 8, 2016, Mr. Zuckerberg had sent go-out-and-vote reminders just to supporters of Mrs. Clinton, that would likely have given her an additional 450,000 votes. I’ve extrapolated that number from Facebook’s own published data.

Because Zuckerberg was overconfident in 2016, I don’t believe he sent those messages, but he is surely not overconfident this time around. In fact, it’s possible that, at this very moment, Facebook and other companies are sending out targeted register-to-vote reminders, as well as targeted go-out-and-vote reminders in primary races. Targeted go-out-and-vote reminders might also favor one party on Election Day in November.

My associates and I are building systems to monitor such things, but because no systems are currently in place, there is no sure way to tell whether Twitter, Google, and Facebook (or Facebook’s influential offshoot, Instagram) are currently tilting their messaging. No law or regulation specifically forbids the practice, and it would be an easy and economical way to serve company needs. Campaign donations cost money, after all, but tilting your messaging to favor one candidate is free.

4. Opinion Matching Effect (OME)
In March 2016, and continuing for more than seven months until Election Day, Tinder’s tens of millions of users could not only swipe to find sex partners, they could also swipe to find out whether they should vote for Trump or Clinton. The website iSideWith.com—founded and run by “two friends” with no obvious qualifications—claims to have helped more than 49 million people match their opinions to the right candidate. Both CNN and USA Today have run similar services, currently inactive.

I am still studying and quantifying this type of, um, helpful service, but so far it looks like (a) opinion matching services tend to attract undecided voters—precisely the kinds of voters who are most vulnerable to manipulation, and (b) they can easily produce opinion shifts of 30 percent or more without people’s awareness.

At this writing, iSideWith is already helping people decide who they should vote for in the 2018 New York U.S. Senate race, the 2018 New York gubernatorial race, the 2018 race for New York District 10 of the U.S. House of Representatives, and, believe it or not, the 2020 presidential race. Keep your eyes open for other matching services as they turn up, and ask yourself this: Who wrote those algorithms, and how can we know whether they are biased toward one candidate or party?

5. Answer Bot Effect (ABE)
More and more these days, people don’t want lists of thousands of search results, they just want the answer, which is being supplied by personal assistants like Google Home devices, the Google Assistant on Android devices, Amazon’s Alexa, Apple’s Siri, and Google’s featured snippets—those answer boxesat the top of Google search results. I call the opinion shift produced by such mechanisms the Answer Bot Effect (ABE).

My research on Google’s answer boxes shows three things so far: First, they reduce the time people spend searching for more information. Second, they reduce the number of times people click on search results. And third, they appear to shift opinions 10 to 30 percent more than search results alone do. I don’t yet know exactly how many votes can be shifted by answer bots, but in a national election in the United States, the number might be in the low millions.

6. Shadowbanning
Recently, Trump complained that Twitter was preventing conservatives from reaching many of their followers on that platform through shadowbanning, the practice of quietly hiding a user’s posts without the user knowing. The validity of Trump’s specific accusation is arguable, but the fact remains that any platform on which people have followers or friends can be rigged in a way to suppress the views and influence of certain individuals without people knowing the suppression is taking place. Unfortunately, without aggressive monitoring systems in place, it’s hard to know for sure when or even whether shadowbanning is occurring.

7. Programmed Virality and the Digital Bandwagon Effect
Big Tech companies would like us to believe that virality on platforms like YouTube or Instagram is a profoundly mysterious phenomenon, even while acknowledging that their platforms are populated by tens of millions of fake accounts that might affect virality.

In fact, there is an obvious situation in which virality is not mysterious at all, and that is when the tech companies themselves decide to shift high volumes of traffic in ways that suit their needs. And aren’t they always doing this? Because Facebook’s algorithms are secret, if an executive decided to bestow instant Instagram stardom on a pro-Elizabeth Warren college student, we would have no way of knowing that this was a deliberate act and no way of countering it.

The same can be said of the virality of YouTube videos and Twitter campaigns; they are inherently competitive—except when company employees or executives decide otherwise. Google has an especially powerful and subtle way of creating instant virality using a technique I’ve dubbed the Digital Bandwagon Effect. Because the popularity of websites drives them higher in search results, and because high-ranking search results increase the popularity of websites (SEME), Google has the ability to engineer a sudden explosion of interest in a candidate or cause with no one—perhaps even people at the companies themselves—having the slightest idea they’ve done so. In 2015, I published a mathematical model showing how neatly this can work.

8. The Facebook Effect
Because Facebook’s ineptness and dishonesty have squeezed it into a digital doghouse from which it might never emerge, it gets its own precinct on my list.

In 2016, I published an article detailing five ways that Facebook could shift millions of votes without people knowing: biasing its trending box, biasing its center newsfeed, encouraging people to look for election-related material in its search bar (which it did that year!), sending out targeted register-to-vote reminders, and sending out targeted go-out-and-vote reminders.

I wrote that article before the news stories broke about Facebook’s improper sharing of user data with multiple researchers and companies, not to mention the stories about how the company permitted fake news stories to proliferate on its platform during the critical days just before the November election—problems the company is now trying hard to mitigate. With the revelations mounting, on July 26, 2018, Facebook suffered the largest one-day drop in stock value of any company in history, and now it’s facing a shareholder lawsuit and multiple fines and investigations in both the United States and the EU.

Facebook desperately needs new direction, which is why I recently called for Zuckerberg’s resignation. The company, in my view, could benefit from the new perspectives that often come with new leadership.

9. Censorship
I am cheating here by labeling one category “censorship,” because censorship—the selective and biased suppression of information—can be perpetrated in so many different ways.

Shadowbanning could be considered a type of censorship, for example, and in 2016, a Facebook whistleblower claimed he had been on a company team that was systematically removing conservative news stories from Facebook’s newsfeed. Now, because of Facebook’s carelessness with user data, the company is openly taking pride in rapidly shutting down accounts that appear to be Russia-connected—even though company representatives sometimes acknowledge that they “don’t have all the facts.”

Meanwhile, Zuckerberg has crowed about his magnanimity in preserving the accounts of people who deny the Holocaust, never mentioning the fact that provocative content propels traffic that might make him richer. How would you know whether Facebook was selectively suppressing material that favored one candidate or political party? You wouldn’t. (For a detailed look at nine ways Google censors content, see my essay “The New Censorship,” published in 2016.)

10. The Digital Customization Effect (DCE)
Any marketer can tell you how important it is to know your customer. Now, think about that simple idea in a world in which Google has likely collected the equivalent of millions of Word pages of information about you. If you randomly display a banner ad on a web page, out of 10,000 people, only five are likely to click on it; that’s the CTR—the “clickthrough rate” (0.05 percent). But if you target your ad, displaying it only to people whose interests it matches, you can boost your CTR a hundredfold.

That’s why Google, Facebook, and others have become increasingly obsessed with customizing the information they show you: They want you to be happily and mindlessly clicking away on the content they show you.

In the research I conduct, my impact is always larger when I am able to customize information to suit people’s backgrounds. Because I know very little about the participants in my experiments, however, I am able to do so in only feeble ways, but the tech giants know everything about you—even things you don’t know about yourself. This tells me that the effect sizes I find in my experiments are probably too low. The impact that companies like Google are having on our lives is quite possibly much larger than I think it is. Perhaps that doesn’t scare you, but it sure scares me.

The Same Direction

OK, you say, so much for Epstein’s list! What about those other shenanigans we’ve heard about: voter fraud (Trump’s explanation for why he lost the popular vote), gerrymandering, rigged voting machines, targeted ads placed by Cambridge Analytica, votes cast over the internet, or, as I mentioned earlier, those millions of bots designed to shift opinions. What about hackers like Andrés Sepúlveda, who spent nearly a decade using computer technology to rig elections in Latin America? What about all the ways new technologies make dirty tricks easier in elections? And what about those darn Russians, anyway?

To all that I say: kid stuff. Dirty tricks have been around since the first election was held millennia ago. But unlike the new manipulative tools controlled by Google and Facebook, the old tricks are competitive—it’s your hacker versus my hacker, your bots versus my bots, your fake news stories versus my fake news stories—and sometimes illegal, which is why Sepúlveda’s efforts failed many times and why Cambridge Analytica is dust.

“Cyberwar,” a new book by political scientist Kathleen Hall Jamieson, reminds us that targeted ads and fake news stories can indeed shift votes, but the numbers are necessarily small. It’s hard to overwhelm your competitor when he or she can play the same games you are playing.

Now, take a look at my numbered list. The techniques I’ve described can shift millions of votes without people’s awareness, and because they are controlled by the platforms themselves, they are entirely noncompetitive. If Google or Facebook or Twitter wants to shift votes, there is no way to counteract their manipulations. In fact, at this writing, there is not even a credible way of detecting those manipulations.

And what if the tech giants are all leaning in the same political direction? What if the combined weight of their subtle and untraceable manipulative power favors one political party? If 150 million people vote this November in the United States, with 20 percent still undecided at this writing (that’s 30 million people), I estimate that the combined weight of Big Tech manipulations could easily shift upwards of 12 million votes without anyone knowing. That’s enough votes to determine the outcomes of hundreds of close local, state, and congressional races throughout the country, which makes the free-and-fair election little more than an illusion.

Full disclosure: I happen to think that the political party currently in favor in Silicon Valley is, by a hair (so to speak), the superior party at the moment. But I also love America and democracy, and I believe that the free-and-fair election is the bedrock of our political system. I don’t care how “right” these companies might be; lofty ends do not justify shady means, especially when those means are difficult to see and not well understood by either authorities or the public.

Can new regulations or laws save us from the extraordinary powers of manipulation the Big Tech companies now possess? Maybe, but our leaders seem to be especially regulation-shy these days, and I doubt, in any case, whether laws and regulations will ever be able to keep up with the new kinds of threats that new technologies will almost certainly pose in coming years.

I don’t believe we are completely helpless, however. I think that one way to turn Facebook, Google, and the innovative technology companies that will succeed them, into responsible citizens is to set upsophisticated monitoring systems that detect, analyze, and archive what they’re showing people—in effect, to fight technology with technology.

As I mentioned earlier, in 2016, I led a team that monitored search results on multiple search engines. That was a start, but we can do much better. These days, I’m working with business associates and academic colleagues on three continents to scale up systems to monitor a wide range of information the Big Tech companies are sharing with their users—even the spoken answers provided by personal assistants. Ultimately, a worldwide ecology of passive monitoring systems will make these companies accountable to the public, with information bias and online manipulation detectable in real time.

With November drawing near, there is obviously some urgency here. At this writing, it’s not clear whether we will be fully operational in time to monitor the midterm elections, but we’re determined to be ready for 2020.

Dr. Robert Epstein is a senior research psychologist at the American Institute for Behavioral Research and Technology in California.

The citizens demanded an FTC task force and they got one launched: The Federal Trade Commission will be launching a task force to monitor competition in the US’s technology markets, FTC commissioners announced.

The task force will include current officials working in the agency’s Bureau of Competition in order to “enhance the Bureau’s focus on technology-related sectors of the economy, including markets in which online platforms compete.” It will also include 17 staff attorneys who will be tasked with investigating anti-competitive behavior in the tech industry.

“The role of technology in the economy and in our lives grows more important every day,” FTC Chairman Joe Simons said. “As I’ve noted in the past, it makes sense for us to closely examine technology markets to ensure consumers benefit from free and fair competition.”

“Technology markets … raise distinct challenges for antitrust enforcement”

The new task force comes amid growing pressure for antitrust action against large tech companies like Facebook and Google. Earlier this month, it was reported that FTC officials have been looking to levy a multibillion-dollar fine on Facebook for repeatedly violating a privacy agreement the two bodies came to back in 2011. A coalition of advocacy groups argued that a fine would not be enough to incentivize Facebook to be more cautious with consumer data and asked the FTC to force the company spinoffs, Instagram and WhatsApp, back into their own entities once again. The groups argued that Facebook was too big for it to adequately care for user data for all three major apps.

Discussion over retroactive merger reviews that may result in companies divesting previously approved assets has been heating up over the last few months. The Democratic-led House Judiciary Committee has been reportedly beefing up its antitrust arm and hiring on big names like Lina Khan in the academic sphere.

“Technology markets, which are rapidly evolving and touch so many other sectors of the economy, raise distinct challenges for antitrust enforcement,” said Bureau Director Bruce Hoffman. “By centralizing our expertise and attention, the new task force will be able to focus on these markets exclusively – ensuring they are operating pursuant to the antitrust laws, and taking action where they are not.”

Hoffman confirmed that the task force would look into consummated mergers, but could not name any investigations specifically. When it comes to remedies for problematic mergers, Hoffman said that firms could be “broken out,” or could be forced to “spin off” previous acquisitions as new competitors in order to recreate the markets pre-merger.

Hoffman said that the task force would be working closely with the FTC’s Consumer Protection Bureau as it relates to consumer privacy enforcement especially in cases in which these issues coalesce.

“Our ongoing Hearings on Competition and Consumer Protection in the 21st Century are a crucial step to deepen our understanding of these markets and potential competitive issues. The Technology Task Force is the next step in that effort,” Simons said in the press release.

The Justice Department, which also has antitrust jurisdiction, is aware of the FTC’s new task force, according to Hoffman, and both agencies will continue to work separately on this front.

An alliance of investigators, forensics experts, EU prosecution offices, FBI specialists, journalists, voters and public crowd-sourced volunteers have been campaigning for the arrest, prosecution, exposure and termination of each and every company, group and individual who engaged in these crimes and reprisal attacks on those who reported them.

It has aready cost the oligarchs their power and their cash, ie: https://www.usnews.com/news/world/articles/2019-02-27/billionaire-list-shows-1t-hit-from-18-market-meltdown

“WINNING”, in this case, means punching the bad guys in the legal nose and teaching every other citizen how to do it too!

ANTI-CORRUPTION Action Items Check List:

1.) Build The Internet (Done)

2.) Put Movies And Music On The Internet To Get All Of The Base Demographics And Nose Pickers To Come To A Collaborative Global Network (Done)

3.) Give Everybody On Earth All Of The Secrets About How Abused And Manipulated They Are By A Handful of Evil Billionaires (Done)

4.) Expose The Manipulative Fraud Of Political Party Bosses (Done)

5.) Tell The Entire Planet, 1 Million People At A Time, How The Billionaires Companies Abuse Their Privacy, Minds, Human Rights and Media Impressions (Done)

6.) Crash All of the Billionaires Main Stream “Fake News” Information Outlets by Exposing Them And Giving All News Away For Free And Teaching People How To Make Free Newspapers (Done)

7.) Crash the Evil Billionaires Silicon Valley Companies, and Money, By Contacting 1 Million People at a Time to Remind Them to Boycott Silicon Valley Companies and Their Products (Done)

8.) Contact Every Advertiser of Every Silicon Valley Billionaire and Warn Them To Pull All Ad Budgets For the Companies Who Contribute to Political Campaigns (In Process)

9.) Make It So That Non-Main-Stream Candidates Can Run And Win By Exposing And Breaking Illicit Election Rigging (Done)

10.) Sit Back And Watch The Fireworks (In Process)


NEW AI SOFTWARE THAT EXPOSES CROOKS IN PUBLIC OFFICE

– New open-source, and free, public software let’s any citizen get any corrupt official arrested. Any voter can use the software from the comfort of their living room. The AI replicates itself (Like A benign digital version of Covid) across the entire web.

– You can download a copy of the software or build-your-own version of it from freely available code at Github, CERN and Linux repositories.

– We have consulted to the SEC and the GAO on this technology.

– After suffering millions of dollars of losses from public official’s Insider Trading schemes, we decided to do something about that!

Illegal and corrupt Congressional insider trading tends to be something we don’t hear about until it’s hit the big news networks and newspapers as the SEC goes for the throat of the accused. By then, unfortunately, those committing it have made their gains, usually in the multi-millions of dollars, and the damage has been done to the stock, its company, investors and the American Way. Covert stock market trades are now the #1 form of bribes in California and Washinton, DC.

Quite frankly, the jail time assessed doesn’t correct the damage done, and the fines rarely aid the investors, or the voters, in getting their money and their democracy back. Many of those hurt are Average Joe’s and Jill’s who were just trying to save their retirement nest eggs. Shame is the tool that works best on the corrupt!

These crimes involve an investment banker spouse and a Senator or other top official, using information, which was not available to the public, buying and selling a company’s stock in an underhanded manner. In many cases bribes have been paid with Google, Tesla or Facebook stock in a covert manner. It is particularly onerous when a Senators buys Tesla, Google, Facebook or Solyndra stock, and makes laws that only benefits Tesla, Solyndra, etc, while sabotaging their competitor constituents. Because the dealings involved are pretty much done on the sly, it’s been difficult, until now, for the governing body of the SEC to prove illegal insider trading, unless one of the cohorts tattles on the others or their actions become glaringly obvious. In some cases, a sharp mind around the action may take notice and become what’s called a whistle-blower.

Previously, writes Andrew Beattie of Investopedia: “... insider trading is often difficult for the SEC to spot. Detecting it involves a lot of conjecture and consideration of probabilities.” That was the ‘old days‘, though. Today, the new AI software can bust through these scams like a hot knife through butter!

With this new open-source, free, public spy agency-class software, detecting illegal insider trading is actually less complicated than it sounds.

To the eyes of this new super-powerful AI observer server bot and peer-to-peer databases, it is easy work.

You, the citizen, just type the politician or agency employee name into a field and hit the “analyze” button. A few minutes later you receive a multi-page PDF report similar to an FBI report on the target. You can either research the subject in more detail or send copies of the report to the FBI, GAO, OSC, SEC or other enforcement group.

The software is an automated AI temporal matching system which includes 24/7 analysis of all stock trades involving politicians to its information source, politician finances, communications and policy participators. it uses some of the same software code used by the CERN mega-research center in Switzerland.

The technology Core Evaluation Points:

  • Analyst estimates – these come from what an analyst estimates that a company’s quarterly or annual earnings will be. They are important because they help approximate the fair value of an entity, which basically establishes it price on the stock exchange.
  • Share volume – this reflects the quantity of shares that can be traded over a certain period of time. There are buyers and there are sellers, and the transactions that take place between them contribute to total volume.

One Way The AI Detects Congressional Insider Trades

Metricized signs of illegal insider trading occur when trades occur that break out of the historical pattern of share volume traded compared to beneficiary participation’s of those connected to company and political entity. Another clue of the illegal insider trading is when a lot of trading goes on right before earnings announcements. That tends to be a sign that someone already knows what the announcement is going to indicate, and it’s an obvious violation. One module of the new software hunts these trends around-the-clock in an unmanned manner like a detective who never needs to sleep.

The software red alerts are issued when trades are linked closer to the actual earnings and politicians bills instead of what the predicted earnings were. In a corruption case, it’s clear the trades – especially made by politicians close to the company – stemmed from information that was not readily available to the general public.

In other words, at the time an insider makes a trade, the trade has a stronger relationship to earnings guidance rather than to earnings results achieved.

Part Of The Insider Trading Detection AI Uses ‘Dynamic Time Warping (DTW)’

In econometrics, which is a concept frequently used by quantitative analysts to evaluate stock market prices, dynamic time warping (DTW) is an algorithm that can be used for measuring similarity between two data sequences by calculating an optimal match between the two. This sequence “matching” method is often used in time series classification to properly “line things up.”

The method, coupled with AI machine learning ensemble methods, can provide a clear path between the trades made by insiders and public data used to make the trades.

This is a product of artificial intelligence that has been expanded by Indexer, Splunk, Palantir and other firms fast becoming experts in products that can be used to advance the art of manipulating political and social trends in business and markets by using social media, financial data and news stories. The new software process has taken that sort of approach to the next level and targeted every member of Congress, their staff, family and friends. The first emphasis is on California and Washington, DC public figures.

In a hypothetical example, a group of executives failed to trade by industry standards by leveraging material non-public information and policy manipulation. Although consensus estimates called for higher commodity prices at the end of 2015, it appears key executives traded for their personal accounts as a result of the forecast provided by a specialist system within the firm that was adept at predicting prices alongside lobbyist manipulations. Flash-boy trading is now dirtier and powered by Google-class server systems.

In the hypothetical scenario the software aggregates executive trades in 2014 and 2015 and finds a strong link between buys and sells of executive stock options, which line up with material non-public estimates of commodity prices that were provided by the specialist system.

For example, in a “Exec Sell and Exec Buys” graph, a green line represents sells, while a black line represents buys. In the corresponding period, one finds a red line represents unrevised prices provided by the specialist system, and green line represents consensus estimates.

During Q1-2014, there was $28M in purchases of executive stock options, while in Q2-2014, there was $25M in sales of executive stock options. The specialist system called for Q3-2014 commodity prices to make a precipitous decline going into the end of 2014. Remember, under this scenario, no revisions were made to the specialist systems’ price forecast. In this example, executives were afforded a significant advantage using price predictions from the specialist system.

In a final bullet chart, there was a dynamic time warping distance between trades and consensus estimates of 7.23, but this distance is only 2.19 when comparing specialist system estimates and executive trades. Please note, the closer the distance score is to zero, the more similar the trades are to the estimates they are measured against.

We have applied this process to companies well-known for influence buying like, Google, Tesla and Facebook

It’s obvious that the tech executives involved did not follow industry standards in their actions and make public the “insider” information they had access to prior to the trades they made. The lobbyists they hired promoted this rigged trend and paid off Senators with perks. These are the kind of violations the SEC and other governing bodies can look to in attempting to protect the trading public and the integrity of financial marketplaces. Artificial intelligence tools are a major factor in assisting the tracking of insider trading.

“Every facet of our everyday lives has been impacted, infiltrated and greatly influenced by artificial intelligence technologies,” says Vernon A. McKinley, a multi-jurisdictional attorney, based in Atlanta. “In fact, the U.S. government and its multiple agencies have developed specialized intelligence units to detect, track, analyze and prosecute those unscrupulous individuals seeking to profit from the use of such tools, specifically in the financial industry, and to protect the integrity and strength of the U.S. economy and its investors.” Now these tools are being turned against the corrupt!

The public can now detect trading anomalies in financial situations using this artificial intelligence software on their desktop computers. No public official will ever be able to do these kinds of corruptions, again, without getting caught.

This approach has already had an impact on how political insiders trade on Wall Street and in financial markets around the world.

This technology can end this corruption forever!

A module of the software uses data from The Center for Responsive Politics, ICIJ Panama Leaks records, Swiss Leaks records and FEC files to reveal covert routes. Famous politicians own part of Tesla Motors, Facebook, Google, Netflix, YouTube and other companies they helped get government money for. All of their competing constituents have suffered for it or been put out of business by exclusive deals that only Tesla Motors, Facebook, Google, Netflix and YouTube got. That is a crime and charges have been filed with federal law enforcement.

A large volume of forensic research proves that Silicon Valley Cartel tech firms receive benefits from politicians and politicians,at the same time, benefit from these firms.

This evidence on the exchange of benefits between politicians and firms proves an agreement between the politicians and the companies. This agreement, however, cannot be in the form of a written contract as writing direct fee-for-service contracts between a politician and a firm is considered bribery (Krozner and Stratmann 1998; 2000). In addition, either party to this agreement might renege on its promise and the other party cannot resort to the courts.

Procon.org, for example, reports: “Less than two months after ascending to the United States Senate, and before becoming President, one Senator bought more than $50,000 worth of stock in two speculative companies whose major investors included some of his biggest political donors. One of the companies was a biotech concern that was starting to develop a drug to treat avian flu. In March 2005, two weeks after buying thousands of dollars of its shares, this Senator took the lead in a legislative push for more federal spending to battle the disease. The most recent financial disclosure form this Senator . . . shows that he bought more than $50,000 in stock in a satellite communications businesswhose principal backers . . . had raised more than $150,000 for his political committees.” See more examples from the Citizens for Responsibility and Ethics in Washington (CREW) report (2009).)

The literature and eye-witness experience proves that politically-connected Silicon Valley tech firms monthly obtain economic favors, such as securing favorable legislation, special tax exemptions, having preferential access to finance, receiving government contracts, or help in dealing with regulatory agencies. The evidence proves that Google’s support, for example, can help in winning elections. For example, firms can vary the number of people they employ, coordinate the opening and closing of plants, and increase their lending activity in election years in order to help incumbent politicians get re-elected. (SeeRoberts 1990; Snyder 1990; Langbein and Lotwis 1990; Durden, Shorgen, and Silberman 1991; Stratmann 1991, 1995, and 1998; Fisman 2001;Johnson and Mitton 2003; Ansolabehere, Snyder, and Ueda 2004; Sapienza 2004, Dinç 2005; Khwaja and Mian 2005; Bertrand, Kramarz,Schoar, and Thesmar 2006; Faccio 2006; Faccio, Masulis, and McConnell 2006; Jayachandran 2006; Leuz and Oberholzer-Gee 2006; Claessens,Feijen, Laeven 2008; Desai and Olofsgard 2008; Ramanna 2008;Goldman, Rocholl, and So 2008, 2009; Cole 2009; Cooper, Gulen, and Ovtchinnikov 2009; Correia 2009; Ramanna and Roychowdhury 2010;Benmelech and Moskowitz 2010.)

The software can see that the share ownership of politicians serves as a mechanism to quid-pro-quo their relationships with big tech firms, is as follows: The ownership of politicians plays multiple distinct (but not necessarily independent) roles; one that relies upon the amount of ownership and one that does not. First, as investors in firms, politicians tie their own interests to those of the firm. Thus, harming (benefiting) the firm means harming (benefiting) the politician and vice versa. By owning a firm’s stock, politicians commit their personal wealth to the firm and reduce a firm’s uncertainty with regard to their actions toward the firm. This will,in turn, enhance the firm’s incentive to support the politician-owner during both current and future elections in order to prolong the incumbency period for as long as possible. Firms have their lobbyists push to be able to know the amount of ownership likely to be material to politicians. This knowledge, in turn, enables them to judge whether the politician’s interest is aligned with the firm’s interest and optimize quid-pro-quo.

The Political Action Committee (PAC) contribution of firms (which is a direct measure of benefits flowing from firms to politicians) is a significant determinant of ownership allocations by members of Congress. The ownership of Congress members in firms that contribute to their election campaigns is roughly 32.8% higher than their ownership in noncontributing firms even after accounting for factors that are associated with both ownership and contribution (such as familiarity, proximity and investor recognition).

The committee assignments of politicians is a proxy for whether their relations with firms are enforced (Krozner and Stratmann 1998). Silicon Valley tech firms like Facebook, Tesla and Google obtain private benefits out of their mutual relations with politicians. When the strength of the association between ownership and contributions at the firm level increases, the provision of government contracts to those firms increases.

Members of Congress, candidates for federal office, senior congressional staff, nominees for executive branch positions, Cabinet members, the President and Vice President, and Supreme Court justices are required by the Ethics in Government Act of 1978 to file annual reports disclosing their income, assets, liabilities, and other relevant details about their personal finances.

Personal financial disclosure forms are filed annually by May 15 and cover the preceding calendar year. The Center for Responsive Politics (CRP) collected the 2004–2007 reports for Congress members from the Senate Office of Public Records and the Office of the Clerkof the House. The Center then scanned the reports as digital images, classified the politicians’ investments into categories including stocks, bonds, and mutual funds, and built a database accessible via a web query.

Using CRP’s data, you can use the software to collect the shares in S&P 500 firms held by members of Congress between 2004 and 2007, for example.You can collect the stock ownership data for every firm that joined the S&P 500 Index any time between January 2004 and April 2009;regardless of when it joined the index,  and the software can obtain all the available stock ownership data for that firm between 2004 and 2007. Likewise, if a firm dropped out of the index at any time during 2004–2008, the software, nevertheless, will retain the firm in a sample for the target period. As such, the sample would include stocks in hundreds of unique firms owned by politicians between 2004 and 2007, for example.

Politicians are required to report only those stocks whose value exceeds $1,000 at the end of the calendar year or that produce more than $200 in income. They are CURRENTLY not required to report the exact value of the holding, but instead must simply check a box corresponding to the value range into which the asset falls. The CRP then undertakes additional research to determine the exact values of these stocks. When the Center makes these determinations, it reports them instead of the ranges and I use these values in my study. When only the range is available, you should use its midpoint as the holding’s value. You would, thus have data on the stock holdings of hundreds politicians for that time period.

Using the software, you can search for all Political Action Committees (PACs) associated with tech firms. It then collects data on each contribution these PACs made to candidates (both the winners and losers) running for the Senate and House elections. Tricky corrupt Silicon Valley firms establish several PACs, each in a different location, and each of these PACs can contribute to the same candidate. In such cases, the software would total, for each candidate, every contribution he or she received from PACs affiliated with the same firm. To parallel the investment data sample period, for example, the software collects every contribution made from the 2003–2004 cycle up to and including the 2007–2008 cycle. Many Silicon Valley tech firms use deeply covert Fusion GPS, Perkins Coie, BlackCube, Psyops-type service to make very hidden additional payola payments to California politicians.

For sources, for example, the software collects government contract data from Eagle Eye Publishers, Inc., one of the leading commercial providers of Federal procurement and grant business intelligence and http://www.usaspending.org. Eagle Eye collects its contract data from Federal Procurement Data System–Next Generation (FPDS-NG), the contract data collection and dissemination system administered by the U.S. General Services Administration (GSA). FPDS-NG provides data on procurement contracts awarded by the U.S. Government. When these contracts are awarded to company subsidiaries, Eagle Eye searches for the names of their parent companies and assigns each subsidiary to its appropriate parent. The software collects both the number and aggregate value of government contracts that were awarded to sample firms between 2004 and 2007 in this example time-frame..

The software reveals, for example, that one Representative is a ten-term member of Congress and a senior member of the House Financial Services Committee. They arranged a meeting between the Department of Treasury and One United Bank, a company with close financial ties to themselves, involving both investments and contributions.

“In September 2008, the Representative asked then-Secretary of the Treasury Henry Paulson to hold a meeting for their friends in banks that had suffered from Fannie Mae and Freddie Mac losses.

The Treasury Department complied and held a session with approximately a dozen senior banking regulators, representatives from those banks, and their trade association. Officials of One United Bank have close ties to the Representative and attended the meeting along with the Representative’s chief of staff. Kevin Cohee, chief executive officer of One United, used the meeting as an opportunity to ask for bailout funds.

. . . Former White House officials stated they were surprised when One United Officials asked for bailout funds. . . . In December 2008, the Representative intervened again, asking Treasury to host another meeting to ensure their banks received part of the $700 billion allocated under the Troubled Asset Relief Program. . . . Within two weeks, on December 19, 2008, One United secured $12.1million in bailout funds. . . . This was not the first time the Representative used their position to advance the interests of the bank. the Representative’s spouse became a shareholder in One United in 2001, when it was known as the Boston Bank of Commerce. In 2002, Boston Bank of Commerce tried to purchase Family Savings, a friend of the Representative in Los Angeles. Instead, Family Savings turned to a bank in Illinois. The Representative tried to block the merger by contacting regulators at the FDIC. The Representative publicly stated they did not want a major bank to acquire a bank that the Representative was friends with.

When the Representative’s efforts with the FDIC proved fruitless, the Representative began a public pressure campaign with other community leaders. Ultimately,when Family Savings changed direction and allowed Boston Bank of Commerce to submit a winning bid, the Representative received credit for the merger. The combined banks were renamed One United. . . . In March 2004, the Representative acquired One United stock worth between $250,001 and $500,000, and the Representative’s spouse purchased two sets of stock, each worth between $250,001 and $500,000. In September 2004, the Representative sold their stock in One United and their husband sold a portion of his. That same year, the husband joined the bank’s board. . . . One United Chief Executive Kevin Cohee and President Teri Williams Cohee have donated a total of $8,000 to the Representative’s campaign committee. . . .On October 27, 2009, less than two months before One United received a $12 million bailout, the bank received a cease-and-desist order from the FDIC and bank regulatory officials in Massachusetts for poor lending practices and excessive executive compensation . . . the bank provided excessive perks to its executives, including paying for Mr. Cohee’s use of a $6.4 million mansion . . .” (Ref: CREW report 2009,pp. 123–125)

Thanks to Crony quid-pro-quo revelations by an earlier version of the software, you can also see that Fisker Automotive, Inc.’s $529 Million U.S. Taxpayer Loan Approval by the Department of Energy was dirty. Fisker Automotive’s Chief Operating Officer Bernhard Koehler pleaded with the Department of Energy in a panicked Saturday midnight hour email to receive a $529 million loan as the company was 2 weeks from Chapter 7 liquidation, that it was laying off most of its employees, that no private sector investors would fund the company without DOE guarantees, and that Fisker was unable to raise any further equity funding from independent private-sector investors given the company’s financial condition.These statements were made to a Loan Officer at the DOE . No private sector Loan underwriting (approval) committee would ever grant a low interest loan to a desperate buyer that had just confessed it was in a state of insolvency and was about to layoff most of its staff. Yet within a few weeks the DOE would approve a $529 Million Credit Facility to Fisker. Despite the DOE Loan Officer official’s sworn testimony at April 24th’s House Oversight Committee that the DOE used “same private sector underwriting standards when approving Fisker and other approved Taxpayer Funded Loans” – likely perjury based in documents.

In a ‘U.S. GOVERNMENT CONFIDENTIAL EMAIL’: FISKER AUTOMOTIVE: August 2009: Co-Founder Bernhard Koehler emails U.S. Dept. of Energy Loan Officer in Sat. midnight Panic admitting VC Firms all declined to invest, and company is out of cash. Weeks later the U.S.Department of Energy approves $529M U.S. Taxpayer Funded Loans to FISKER. NO PRIVATE SECTOR Lender would every authorize a Loan for even $5 Million let alone $529 Million after receiving this email stating private sector investors had examined the company and declined equity investments, that they might loan money as more secure Debt, and the Chief Operating Officer of the company further stating that the borrower is totally insolvent. (Weeks after this email the U.S. Federal Government Dept. of Energy Loan Committee Approves Fisker Automotive as a credit-worthy borrow for $529 Million in U.S. Taxpayer Funded Loans). Fisker got the cash because President Obama said to “give it to them” in order to please his campaign financiers.

The same thing happened with Tesla Motors. Elon Musk and Tesla Motors were broke when DOE gave them the money.

PrivCo CEO Sam Hamadeh stated in an official statement: “The documents obtained by PrivCo paint a picture of how an insolvent,unproven automaker received $192 million in taxpayer funding. The Department of Energy made a loan that no rational lender would have made. This loan was the equivalent of staying execution on a company that was terminally ill to begin with.” Tesla and Fisker could not have been taxpayer funded unless bribes and criminal quid-pro-quo was underway by President Obama and the U.S. Senator insider traders.

Since its ruling in Buckley v. Valeo, the U.S. Supreme Court has expressed concern regarding corruption or the appearance of corruption stemming from political quid pro quo arrangements and the deleterious consequences it may have on citizens’ democratic behavior. However, no standard has been set as to what constitutes “the appearance of corruption,” as the Court was and continues to be vague in its definition. As a result, campaign finance cases after Buckley have relied on public opinion polls as evidence of perceptions of corruption, and these polls indicate that the public generally perceives high levels of corruption in government. The present study investigates the actual impact that perceptions of corruption have on individuals’ levels of political participation. Adapting the standard socioeconomic status model developed most fully by Verba and Nie (1972), an extended beta-binomial regression estimated using maximum likelihood is performed, utilizing unique data from the 2009 University of Texas’ Money and Politics survey. The results of this study indicate that individuals who perceive higher levels of quid pro quo corruption participate more in politics, on average, than those who perceive lower levels of corruption.

SOURCE CODE RESOURCES FOR YOU TO FORK:

Spoke: Spoke is a peer-to-peer texting platform for collaborative investigation with several forks under active development.
Pollaris, A polling location lookup tool modified to track bad guys. You can integrate this with your website and other tools. An API is provided.
Caucus App: A way to quickly calculate citizen and pro member evidence sets and report results from each investigator.
-Switchboard (FE and BE): This software takes new potential volunteers, or “hot leads,” from your online channels and assigns them to state or section-based based volunteer leads for personal follow up calls offering ways to get involved with the investigations. This is also a great tool for investiagtion team recruitment.
Automated organizing email: Your teams can work together to scale email outreach to the widest possible audience and bypass any cover-up.
Redhook: Investigations run on data, and redhook is a tool that makes data happen. As a system, Redhook ingests web hook data and delivers it to Redshift/Civis in near real time.
I90: This tool makes a long file name or hard to remember legal evidence document into a short, easy-to-remember, link.
opendata.cern.ch: The CERN Database Open Source
https://github.com: One of the collaborative development nets
https://citizensleuths.com: An example of over 1000 public forensic groups working on crowd-sourced crime-fighting

You are building a forensic anti-corruption version of XKEYSCORE and submitting your results reports to law enforcement and news outlets. Simply look in torrents and code databases like GITHUB, and similar sites, for forensic database and mass collaboration code and you will have a working module up in no time at all if you are a Tier 2 coder, or better.

Summary
Amateur Web Sleuths are Solving Cold Cases, You can Too! Read How
Article Name
Amateur Web Sleuths are Solving Cold Cases, You can Too! Read How
Description
The Skeleton Crew: How Amateur Sleuths Are Solving America’s Coldest Cases, by Deborah Halber, describes how amateur web sleuths are helping with cold cases.
Author
Anne P. Mitchell