AI Now Institute
In plain wordsA research and advocacy group that examines who is harmed by AI and argues that the deeper problem is the power of a few big technology companies, which it wants curbed by law.
A policy research institute whose analysis of AI centers less on the technology itself than on who controls it and who bears its costs. Its early work documented algorithmic biasalgorithmic bias, n.: Unfairness in software that judges or serves people: it consistently produces worse results for some groups, such as women, older people or ethnic minorities, often because it learned from skewed or incomplete records. and the use of automated systems in criminal justice, welfare and employment, and it proposed the algorithmic impact assessmentalgorithmic impact assessment, n.: A structured review, done before and during the use of an automated system, of whom it could affect and how — such as unfair treatment or privacy harms — and what will be done about it. as an accountability tool for public agencies (2018). Its annual reports and later policy work argue that AI's harms stem as much from industry structure as from technical flaws, emphasizing market concentration of powerconcentration of power, n.: The worry that AI will put enormous economic, political or military power in the hands of a few companies, governments or individuals, beyond the reach of ordinary checks and balances. over data and compute, labor, surveillance and the environmental costs of data centersAI data center, n.: A building or campus packed with AI chips, power equipment and cooling, built to train and run AI models. The biggest use as much electricity as a city., and call for using competition and privacy law against what it terms tech power. In debates framed around existential riskexistential risk, n.: A danger that could end humanity, or shut it out of a good future forever. Some experts count advanced AI among the largest such risks; others think this worry is overblown., it argues that present-day harms deserve priority.
Origin
Founded in 2017 at New York University by Kate Crawford and Meredith Whittaker, following a 2016 symposium they organized with the White House Office of Science and Technology Policy. It later became independent of NYU, with Amba Kak and Sarah Myers West as co-executive directors.
Related
- algorithmic biasalgorithmic bias, n.: Unfairness in software that judges or serves people: it consistently produces worse results for some groups, such as women, older people or ethnic minorities, often because it learned from skewed or incomplete records.
- algorithmic impact assessmentalgorithmic impact assessment, n.: A structured review, done before and during the use of an automated system, of whom it could affect and how — such as unfair treatment or privacy harms — and what will be done about it.
- AI ethicsAI ethics, n.: The study of what is right and wrong in how AI is built and used: who it may harm, who is responsible when it fails, and which values it should respect.
- concentration of powerconcentration of power, n.: The worry that AI will put enormous economic, political or military power in the hands of a few companies, governments or individuals, beyond the reach of ordinary checks and balances.
- Distributed AI Research InstituteDistributed AI Research Institute, prop. n.: Timnit Gebru set up this institute in 2021, a year after her departure from Google, to research the damage AI can do, especially to marginalized communities, without relying on big-tech money.
Mentioned in
Distributed AI Research InstituteDistributed AI Research Institute, prop. n.: Timnit Gebru set up this institute in 2021, a year after her departure from Google, to research the damage AI can do, especially to marginalized communities, without relying on big-tech money., Kate CrawfordKate Crawford, prop. n.: An Australian scholar who studies the social, political and environmental costs of AI, co-founded the AI Now Institute, and wrote 'Atlas of AI'.