AI Causes Real Harm. Let's Focus on That over the End-of-Humanity Hype - Scientific Ame... - 0 views
www.scientificamerican.com/...ot-imaginary-existential-risks
opinion analysis AI class race computing propaganda science
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Wrongful arrests, an expanding surveillance dragnet, defamation and deep-fake pornography are all actually existing dangers of so-called “artificial intelligence” tools currently on the market. That, and not the imagined potential to wipe out humanity, is the real threat from artificial intelligence.
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Beneath the hype from many AI firms, their technology already enables routine discrimination in housing, criminal justice and health care, as well as the spread of hate speech and misinformation in non-English languages. Already, algorithmic management programs subject workers to run-of-the-mill wage theft, and these programs are becoming more prevalent.
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Corporate AI labs justify this posturing with pseudoscientific research reports that misdirect regulatory attention to such imaginary scenarios using fear-mongering terminology, such as “existential risk.”
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Because the term “AI” is ambiguous, it makes having clear discussions more difficult. In one sense, it is the name of a subfield of computer science. In another, it can refer to the computing techniques developed in that subfield, most of which are now focused on pattern matching based on large data sets and the generation of new media based on those patterns. Finally, in marketing copy and start-up pitch decks, the term “AI” serves as magic fAIry dust that will supercharge your business.
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output can seem so plausible that without a clear indication of its synthetic origins, it becomes a noxious and insidious pollutant of our information ecosystem
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the people selling this technology propose that text synthesis machines could fix various holes in our social fabric: the lack of teachers in K–12 education, the inaccessibility of health care for low-income people and the dearth of legal aid for people who cannot afford lawyers, just to name a few
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Not only do we risk mistaking synthetic text for reliable information, but also that noninformation reflects and amplifies the biases encoded in its training data—in this case, every kind of bigotry exhibited on the Internet. Moreover the synthetic text sounds authoritative despite its lack of citations back to real sources. The longer this synthetic text spill continues, the worse off we are, because it gets harder to find trustworthy sources and harder to trust them when we do.
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the systems rely on enormous amounts of training data that are stolen without compensation from the artists and authors who created it in the first place
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the task of labeling data to create “guardrails” that are intended to prevent an ai system’s most toxic output from seeping out is repetitive and often traumatic labor carried out by gig workers and contractors, people locked in a global race to the bottom for pay and working conditions.
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employers are looking to cut costs by leveraging automation, laying off people from previously stable jobs and then hiring them back as lower-paid workers to correct the output of the automated systems. This can be seen most clearly in the current actors’ and writers’ strikes in Hollywood, where grotesquely overpaid moguls scheme to buy eternal rights to use ai replacements of actors for the price of a day’s work and, on a gig basis, hire writers piecemeal to revise the incoherent scripts churned out by ai.
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too many AI publications come from corporate labs or from academic groups that receive disproportionate industry funding. Much is junk science—it is nonreproducible, hides behind trade secrecy, is full of hype and uses evaluation methods that lack construct validity
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We urge policymakers to instead draw on solid scholarship that investigates the harms and risks of AI—and the harms caused by delegating authority to automated systems, which include the unregulated accumulation of data and computing power, climate costs of model trAIning and inference, damage to the welfare state and the disempowerment of the poor, as well as the intensification of policing agAInst Black and Indigenous families. Solid research in this domAIn—including social science and theory building—and solid policy based on that research will keep the focus on the people hurt by this technology.