Skip to main content

Home/ Dystopias/ Group items tagged labor

Rss Feed Group items tagged

Filter: All | Bookmarks | Topics Simple Middle
Ed Webb

Artificial Intelligence and the Future of Humans | Pew Research Center - 0 views

www.pewinternet.org/...gence-and-the-future-of-humans

AI dystopia prediction future futures computing

shared by Ed Webb on 14 Dec 18 - No Cached
  • experts predicted networked artificial intelligence will amplify human effectiveness but also threaten human autonomy, agency and capabilities
  • most experts, regardless of whether they are optimistic or not, expressed concerns about the long-term impact of these new tools on the essential elements of being human. All respondents in this non-scientific canvassing were asked to elaborate on why they felt AI would leave people better off or not. Many shared deep worries, and many also suggested pathways toward solutions. The main themes they sounded about threats and remedies are outlined in the accompanying table.
  • CONCERNS Human agency: Individuals are  experiencing a loss of control over their lives Decision-making on key aspects of digital life is automatically ceded to code-driven, "black box" tools. People lack input and do not learn the context about how the tools work. They sacrifice independence, privacy and power over choice; they have no control over these processes. This effect will deepen as automated systems become more prevalent and complex. Data abuse: Data use and surveillance in complex systems is designed for profit or for exercising power Most AI tools are and will be in the hands of companies striving for profits or governments striving for power. Values and ethics are often not baked into the digital systems making people's decisions for them. These systems are globally networked and not easy to regulate or rein in. Job loss: The AI takeover of jobs will widen economic divides, leading to social upheaval The efficiencies and other economic advantages of code-based machine intelligence will continue to disrupt all aspects of human work. While some expect new jobs will emerge, others worry about massive job losses, widening economic divides and social upheavals, including populist uprisings. Dependence lock-in: Reduction of individuals’ cognitive, social and survival skills Many see AI as augmenting human capacities but some predict the opposite - that people's deepening dependence on machine-driven networks will erode their abilities to think for themselves, take action independent of automated systems and interact effectively with others. Mayhem: Autonomous weapons, cybercrime and weaponized information Some predict further erosion of traditional sociopolitical structures and the possibility of great loss of lives due to accelerated growth of autonomous military applications and the use of weaponized information, lies and propaganda to dangerously destabilize human groups. Some also fear cybercriminals' reach into economic systems.
  • ...18 more annotations...
  • AI and ML [machine learning] can also be used to increasingly concentrate wealth and power, leaving many people behind, and to create even more horrifying weapons
  • “In 2030, the greatest set of questions will involve how perceptions of AI and their application will influence the trajectory of civil rights in the future. Questions about privacy, speech, the right of assembly and technological construction of personhood will all re-emerge in this new AI context, throwing into question our deepest-held beliefs about equality and opportunity for all. Who will benefit and who will be disadvantaged in this new world depends on how broadly we analyze these questions today, for the future.”
  • SUGGESTED SOLUTIONS Global good is No. 1: Improve human collaboration across borders and stakeholder groups Digital cooperation to serve humanity's best interests is the top priority. Ways must be found for people around the world to come to common understandings and agreements - to join forces to facilitate the innovation of widely accepted approaches aimed at tackling wicked problems and maintaining control over complex human-digital networks. Values-based system: Develop policies to assure AI will be directed at ‘humanness’ and common good Adopt a 'moonshot mentality' to build inclusive, decentralized intelligent digital networks 'imbued with empathy' that help humans aggressively ensure that technology meets social and ethical responsibilities. Some new level of regulatory and certification process will be necessary. Prioritize people: Alter economic and political systems to better help humans ‘race with the robots’ Reorganize economic and political systems toward the goal of expanding humans' capacities and capabilities in order to heighten human/AI collaboration and staunch trends that would compromise human relevance in the face of programmed intelligence.
  • “I strongly believe the answer depends on whether we can shift our economic systems toward prioritizing radical human improvement and staunching the trend toward human irrelevance in the face of AI. I don’t mean just jobs; I mean true, existential irrelevance, which is the end result of not prioritizing human well-being and cognition.”
  • We humans care deeply about how others see us – and the others whose approval we seek will increasingly be artificial. By then, the difference between humans and bots will have blurred considerably. Via screen and projection, the voice, appearance and behaviors of bots will be indistinguishable from those of humans, and even physical robots, though obviously non-human, will be so convincingly sincere that our impression of them as thinking, feeling beings, on par with or superior to ourselves, will be unshaken. Adding to the ambiguity, our own communication will be heavily augmented: Programs will compose many of our messages and our online/AR appearance will [be] computationally crafted. (Raw, unaided human speech and demeanor will seem embarrassingly clunky, slow and unsophisticated.) Aided by their access to vast troves of data about each of us, bots will far surpass humans in their ability to attract and persuade us. Able to mimic emotion expertly, they’ll never be overcome by feelings: If they blurt something out in anger, it will be because that behavior was calculated to be the most efficacious way of advancing whatever goals they had ‘in mind.’ But what are those goals?
  • AI will drive a vast range of efficiency optimizations but also enable hidden discrimination and arbitrary penalization of individuals in areas like insurance, job seeking and performance assessment
  • The record to date is that convenience overwhelms privacy
  • As AI matures, we will need a responsive workforce, capable of adapting to new processes, systems and tools every few years. The need for these fields will arise faster than our labor departments, schools and universities are acknowledging
  • AI will eventually cause a large number of people to be permanently out of work
  • Newer generations of citizens will become more and more dependent on networked AI structures and processes
  • there will exist sharper divisions between digital ‘haves’ and ‘have-nots,’ as well as among technologically dependent digital infrastructures. Finally, there is the question of the new ‘commanding heights’ of the digital network infrastructure’s ownership and control
  • As a species we are aggressive, competitive and lazy. We are also empathic, community minded and (sometimes) self-sacrificing. We have many other attributes. These will all be amplified
  • Given historical precedent, one would have to assume it will be our worst qualities that are augmented
  • Our capacity to modify our behaviour, subject to empathy and an associated ethical framework, will be reduced by the disassociation between our agency and the act of killing
  • We cannot expect our AI systems to be ethical on our behalf – they won’t be, as they will be designed to kill efficiently, not thoughtfully
  • the Orwellian nightmare realised
  • “AI will continue to concentrate power and wealth in the hands of a few big monopolies based on the U.S. and China. Most people – and parts of the world – will be worse off.”
  • The remainder of this report is divided into three sections that draw from hundreds of additional respondents’ hopeful and critical observations: 1) concerns about human-AI evolution, 2) suggested solutions to address AI’s impact, and 3) expectations of what life will be like in 2030, including respondents’ positive outlooks on the quality of life and the future of work, health care and education
Ed Webb

Feminist Apparel and the Myth of the Woke Brand - Racked - 0 views

www.racked.com/...inist-brand-apparel-capitalism

business feminism capitalism ethics opinion analysis

shared by Ed Webb on 19 Jul 18 - No Cached
  • Let Feminist Apparel be a cautionary tale: Brands don’t have the capacity for ideology beyond capitalism. There’s no such thing as a feminist company, and there never has been.
  • framing for-profit commerce as an act of charity or as a meaningful resistance to evil is no less absurd when someone else does it. Any entity lining its pockets by selling only the aesthetic of political action to those whose lives depend on the results of political action is malevolent and amoral, and it’s a practice in use to varying degrees by an ever-expanding number of companies
  • The politics of any company are bad. They’re not all bad in the same way — they exist on a continuum that extends roughly from “not purposely trying to make anyone’s life worse” to “defense contractor” — but the structure of capitalism means that they all need to pay their employees less than their labor is actually worth and find ways to separate consumers from more money than it actually costs to produce and distribute their product.
  • ...4 more annotations...
  • Companies accumulate wealth by taking it from people with less power through various means of subterfuge (that we call it marketing is, in and of itself, marketing), which, even on a small scale, is an activity necessarily uninterested in equality. If capitalism could deliver economic parity — if parity was even part of the ideology’s intent, which it’s not — then Latinx women wouldn’t still make 54 cents on a white man’s dollar several hundred years into the American capitalist experiment.
  • Capitalism is an apparatus that convinced a whole culture that then-worthless clear rocks were the only real way to tell a woman you wanted to marry her, so convincing us that buying a T-shirt from a creep (or from union busters, or polluters, or whoever) is the same as being politically active is comparatively light work
  • Even though there’s no ethical consumption under capitalism, that doesn’t mean all consumer choices are the same. Companies can’t be feminist, but their leaders can make choices that operate on feminist values, like supporting the unionization of their workforces and providing fair wages and comprehensive health care and family leave to all workers. When possible, taking your business to those companies is an ethically superior choice. Capitalism is a global economic order that’s impossible to opt out of on an individual consumer level, but it’s possible to make some of the individual choices therein with integrity, even if you understand that doing so doesn’t move the dial as political action.
  • the only clear-eyed way to regard a corporation is, at best, as an adversary
Ed Webb

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

shared by Ed Webb on 11 Aug 23 - Cached
  • 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.
  • 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.
  • 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.”
  • ...9 more annotations...
  • 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.
  • 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
  • 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.
  • 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
  • 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
  • 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.
  • 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.
  • 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
  • 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.
1 - 4 of 4
Showing 20▼ items per page