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Societal upheaval during the COVID-19 pandemic underscores need for new AI data regulations

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As a long-time proponent of AI regulation that is designed to protect public health and safety while also promoting innovation, I believe Congress must not delay in enacting, on a bipartisan basis, Section 102(b) of The Artificial Intelligence Data Protection Act — my proposed legislation and now a House of Representatives Discussion Draft Bill. Guardrails in the form of Section 102(b)’s ethical AI legislation are necessary to maintain the dignity of the individual.

What does Section 102(b) of The AI Data Protection Act provide and why the urgent need for the federal government to enact it now?

To answer these questions, it is first necessary to understand how artificial intelligence (AI) is being used during this historic moment when our democratic society is confronting two simultaneous existential threats. Only then can the risks that AI poses to our individual dignity be recognized, and Section 102(b) be understood as one of the most important remedies to protect the liberties that Americans hold dear and that serve as the bedrock of our society.

America is now experiencing mass protests demanding an end to racism and police brutality, and watching as civil unrest unfolds in the midst of trying to quell the deadly COVID-19 pandemic. Whether we are aware of or approve of it, in both contexts — and in every other facet of our lives — AI technologies are being deployed by government and private actors to make critical decisions about us. In many instances, AI is being utilized to assist society and to get us as quickly as practical to the next normal.

But so far, policymakers have largely overlooked a critical AI-driven public health and safety concern. When it comes to AI, most of the focus has been on the issues of fairness, bias and transparency in data sets used to train algorithms. There is no question that algorithms have yielded bias; one only need to look to employee recruiting and loan underwriting for examples of unfair exclusion of women and racial minorities.

We’ve also seen AI generate unintended, and sometimes unexplainable, outcomes from the data. Consider the recent example of an algorithm that was supposed to assist judges with fair sentencing of nonviolent criminals. For reasons that have yet to be explained, the algorithm assigned higher risk scores to defendants younger than 23, resulting in 12% longer sentences than their older peers who had been incarcerated more frequently, while neither reducing incarceration nor recidivism.

But the current twin crises expose another more vexing problem that has been largely overlooked — how should society address the scenario where the AI algorithm got it right but from an ethical standpoint, society is uncomfortable with the results? Since AI’s essential purpose is to produce accurate predictive data from which humans can make decisions, the time has arrived for lawmakers to resolve not what is possible with respect to AI, but what should be prohibited.

Governments and private corporations have a never-ending appetite for our personal data. Right now, AI algorithms are being utilized around the world, including in the United States, to accurately collect and analyze all kinds of data about all of us. We have facial recognition to surveil protestors in a crowd or to determine whether the general public is observing proper social distancing. There is cell phone data for contact tracing, as well as public social media posts to model the spread of coronavirus to specific zip codes and to predict location, size and potential violence associated with demonstrations. And let’s not forget drone data that is being used to analyze mask usage and fevers, or personal health data used to predict which patients hospitalized with COVID have the greatest chance of deteriorating.

Only through the use of AI can this quantity of personal data be compiled and analyzed on such a massive scale.

This access by algorithms to create an individualized profile of our cell phone data, social behavior, health records, travel patterns and social media content — and many other personal data sets — in the name of keeping the peace and curtailing a devastating pandemic can, and will, result in various governmental actors and corporations creating frighteningly accurate predictive profiles of our most private attributes, political leanings, social circles and behaviors.

Left unregulated, society risks these AI-generated analytics being used by law enforcement, employers, landlords, doctors, insurers — and every other private, commercial and governmental enterprise that can collect or purchase it — to make predictive decisions, be they accurate or not, that impact our lives and strike a blow to the most fundamental notions of a liberal democracy. AI continues to assume an ever-expanding role in the employment context to decide who should be interviewed, hired, promoted and fired. In the criminal justice context, it is used to determine who to incarcerate and what sentence to impose. In other scenarios, AI restrict people to their homes, limit certain treatment at the hospital, deny loans and penalize those who disobey social distancing regulations.

Too often, those who eschew any type of AI regulation seek to dismiss these concerns as hypothetical and alarmist. But just a few weeks ago, Robert Williams, a Black man and Michigan resident, was wrongfully arrested because of a false face recognition match. According to news reports and an ACLU press release, Detroit police handcuffed Mr. Williams on his front lawn in front of his wife and two terrified girls, ages two and five. The police took him to a detention center about 40 minutes away, where he was locked up overnight. After an officer acknowledged during an interrogation the next afternoon that “the computer must have gotten it wrong,” Mr. Williams was finally released — nearly 30 hours after his arrest.

While widely believed to be the first confirmed case of AI’s incorrect facial recognition leading to the arrest of an innocent citizen, it seems clear this won’t be the last. Here, AI served as the primary basis for a critical decision that impacted the individual citizen — being arrested by law enforcement. But we must not only focus on the fact that the AI failed by identifying the wrong person, denying him his freedom. We must identify and proscribe those instances where AI should not be used as the basis for specified critical decisions — even when it gets it “right.”

As a democratic society, we should be no more comfortable with being arrested for a crime we contemplated but did not commit, or being denied medical treatment for a disease that will undoubtedly end in death over time, as we are with Mr. Williams’ mistaken arrest. We must establish an AI “no-fly zone” to preserve our individual freedoms. We must not allow certain key decisions to be left solely to the predictive output of artificially intelligent algorithms.

To be clear, this means that even in situations where every expert agrees that the data in and out is completely unbiased, transparent and accurate, there must be a statutory prohibition on utilizing it for any type of predictive or substantive decision-making. This is admittedly counter-intuitive in a world where we crave mathematical certainty, but necessary.

Section 102(b) of the Artificial Intelligence Data Protection Act properly and rationally accomplishes this in the context of both scenarios — where AI generates correct and/or incorrect outcomes. It does this in two key ways.

First, Section 102(b) specifically identifies those decisions which can never be made in whole or in part by AI. For example, it enumerates specific misuses of AI that would prohibit covered entities’ sole reliance on artificial intelligence to make certain decisions. These include recruitment, hiring and discipline of individuals, the denial or limitation of medical treatment, or medical insurance issuers making decisions regarding coverage of a medical treatment. In light of what society has recently witnessed, the prohibited areas should likely be expanded to further minimize the risk that AI will be used as a tool for racial discrimination and harassment of protected minorities.

Second, for certain other specific decisions based on AI analytics that are not outright prohibited, Section 102(b) define those instances where a human must be involved in the decision-making process.

By enacting Section 102(b) without delay, legislators can maintain the dignity of the individual by not allowing the most critical decisions that impact the individual to be left solely to the predictive output of artificially intelligent algorithms.

Source: https://techcrunch.com/2020/07/10/societal-upheaval-during-the-covid-19-pandemic-underscores-need-for-new-ai-data-regulations/

Publications

Security and Sustainability Forum-With Hazel Henderson and Claudine Schneider. 10/22/2020

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Steering Societies Beyond GDP to the SDGs

With Hazel Henderson and Claudine Schneider

October 22, 2020

1:15 pm to 2:15 pm EDT

The next webinar in the SSF series, with ecological economist and futurist Hazel Henderson, will address how the UN SDGs can and should replace GDP as the basis for valuing society leading to an economy based on planet protection and human wellbeing. Claudine Schneider is Hazel’s guest.

GDP accounts for all the public expenditures as “debt” while ignoring the value of the assets they created. If GDP were to be corrected by including the missing asset account, these debt-to-GDP ratios would be cut by up to 50% — with a few keystrokes! Learn why money isn’t what you think it is and why that matters to life on Earth in the next two webinars with Hazel and guests.

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Claudine Schneider is a former Republican U.S. representative from Rhode Island. She was the first, and to date only, woman elected to Congress from Rhode Island. She is founder of Republicans for Integrity, which describes itself as a network of “Republican former Members of Congress who feel compelled to remind Republican voters about the fundamentals of our party and to provide the facts about incumbents’ voting records.”

October 22nd webinar with Claudine Schneider and Hazel

Sincerely,

Ed.

Edward Saltzberg, PhD

Executive Director

Security and Sustainability Forum

www.ssfonline.org

[email protected]

Sincerely,

Ed.

Edward Saltzberg, PhD

Executive Director

Security and Sustainability Forum

www.ssfonline.org

Source: https://www.ethicalmarkets.com/63564-2/

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The Briefing: RVShare raises over $100M, Google disputes charges, and more

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Here’s what you need to know today in startup and venture news, updated by the Crunchbase News staff throughout the day to keep you in the know.

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RVShare raises over $100M for RV rentals

RVShare, an online marketplace for RV rentals, reportedly raised over $100 million in a financing led by private equity firms KKR and Tritium Partners.

Akron, Ohio-based RVShare has seen sharp growth in demand amid the pandemic, as more would-be travelers seek socially distanced options for hitting the road. Founded in 2013, the company matches RV owners with prospective renters, filtering by location, price and vehicle types.

Previously, RVShare had raised $50 million in known funding, per Crunchbase data, from Tritium Partners. The company is one of several players in the RV rental space, and competes alongside Outdoorsy, a peer-to-peer RV marketplace that has raised $75 million in venture funding.

Funding news

  • BrightFarms closes on $100M: Indoor farming company BrightFarms said it secured more than $100 million in debt and new equity capital to support expansion plans. The Series E round of funding was led by Cox Enterprises, which now owns a majority stake in the company, and includes a follow-on investment from growth equity firm Catalyst Investors.
  • Anyscale inks $40MAnyscale, the Berkeley-based company behind the Ray open source project for building applications, announced $40 million in an oversubscribed Series B funding round. Existing investor NEA led the round and was joined by Andreessen Horowitz, Intel Capital and Foundation Capital. The new funding brings Anyscale’s total funding to more than $60 million.
  • Klar deposits $15M: Mexican fintech Klar closed on $15 million in Series A funding, led by Prosus Ventures, with participation from new investor International Finance Corporation and existing investors Quona Capital, Mouro Capital and Acrew. The round brings total funding raised to approximately $72 million since the company was founded in 2019. The funds are intended to grow Klar’s engineering capabilities in both its Berlin and Mexico hubs.
  • O(1) Labs rakes in $10.9M: O(1) Labs, the team behind the cryptocurrency Mina, announced $10.9 million in a strategic investment round. Co-leading the round are Bixin Ventures and Three Arrows Capital with participation from SNZ, HashKey Capital, Signum Capital, NGC Ventures, Fenbushi Capital and IOSG Ventures.
  • Blustream bags $3M: After-sale customer engagement company Blustream said it raised $3 million in seed funding for product usage data and digital transformation efforts for physical goods companies via the Blustream Product Experience Platform. York IE led the round of funding for the Worcester, Massachusetts-based company with additional support from existing investors.Pillar secures another $1.5M: Pillar, a startup that helps families protect and care for their loved ones, raised $1.5 million in a seed extension to close at $7 million, The round was led by Kleiner Perkins.

Other news

  • Google rejects DOJ antitrust arguments: In the wake of a widely anticipated U.S. Justice Department antitrust suit against Google, the search giant disputed the charges in a statement, maintaining that: “People use Google because they choose to, not because they’re forced to, or because they can’t find alternatives.”
  • Facebook said to test Nextdoor rival: Facebook is reportedly testing a service similar to popular neighborhood-focused social Nextdoor. Called Neighborhoods, the feature reportedly suggests local neighborhood groups to join on Facebook.

Illustration: Dom Guzman

Venture investors and leaders in the fintech space can visualize a future where such startups will move toward again rebundling services.

Root Inc., the parent company of Root Insurance, launched its initial public offering and is looking at a valuation of as much as $6.34 billion.

Clover Health posted rising revenues and a narrower loss in its most recent financial results, published in advance of a planned public market debut.

Crunchbase News’ top picks of the news to stay current in the VC and startup world.

Source: https://news.crunchbase.com/news/briefing-10-21-20/

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Syte Sees $30M Series C For Product Discovery

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Online shopping has become the norm for most people in 2020, even coaxing traditional retail brands to up their presence to stay competitive. However, now that shoppers can’t see and touch products like they used to, e-commerce discovery has become a crucial element for customer acquisition and retention.

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Enter Syte, an Israel-based company that touts creating the world’s first product discovery platform that utilizes the senses, such as visual, text and voice, and then leverages visual artificial intelligence and next-generation personalization to create individualized and memorable customer experiences, Syte co-founder and CEO Ofer Fryman told Crunchbase News.

To execute on this, the company raised $30 million in Series C funding and an additional $10 million in debt. Viola Ventures led the round and was joined by LG Technology Ventures, La Maison, MizMaa Ventures and Kreos Capital, as well as existing investors Magma, Naver Corporation, Commerce Ventures, Storm Ventures, Axess Ventures, Remagine Media Ventures and KDS Media Fund.

This brings the company’s total fundraising to $71 million since its inception in 2015. That includes a $21.5 million Series B, also led by Viola, in 2019, according to Crunchbase data.

Fryman intends for the new funding to be put to work on product enhancements and geographic expansion. Syte already has an established customer base in Europe, the Middle East and Africa, and will now focus expansion in the U.S. and Asia-Pacific.

Meanwhile, Syte has grown 22 percent quarter over quarter, as well as experienced a 38 percent expansion of its customer base since the beginning of 2020.

“Since we crossed $1 million annual recurring revenue, we have been tripling revenue while also becoming more efficient,” Fryman said. “We can accelerate growth as well as build an amazing technology and solution for a business that needs it right now. We plan to grow further, and even though our SaaS metrics are excellent right now, our goal is to improve them.”

Anshul Agarwal, managing director at LG Technology Ventures, said Syte was an attractive investment due in part to its unique technology.

“They have a deep-learning system and have created a new category, product discovery that will enable online shopping in a way we never had the ability to do before,” Agarwal said. “The product market fit was also unique. We believe in the strong execution by the team and the rapid growth in SaaS. We looked at many different companies, and the SaaS metrics that Syte showed are the strongest we’ve seen in a while.”

Illustration: Li-Anne Dias

Venture investors and leaders in the fintech space can visualize a future where such startups will move toward again rebundling services.

Root Inc., the parent company of Root Insurance, launched its initial public offering and is looking at a valuation of as much as $6.34 billion.

Clover Health posted rising revenues and a narrower loss in its most recent financial results, published in advance of a planned public market debut.

Crunchbase News’ top picks of the news to stay current in the VC and startup world.

Source: https://news.crunchbase.com/news/syte-sees-30m-series-c-for-product-discovery/

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