Suchergebnisse

AbstractAssume that a researcher uncovers a major problem with how social media are currently used. What sort of challenges arise when they must subsequently decide whether or not to use social media to create awareness about this problem? This situation routinely occurs as ethicists navigate choices regarding how to effect change and potentially remedy the problems they uncover. In this article, challenges related to new technologies and what is often referred to as 'Big Tech' are emphasized. We present what we refer to as the AI ethicist's dilemma, which emerges when an AI ethicist has to consider how their own success in communicating an identified problem is associated with a high risk of decreasing the chances of successfully remedying the problem. We examine how the ethicist can resolve the dilemma and arrive at ethically sound paths of action through combining three ethical theories: virtue ethics, deontological ethics and consequentialist ethics. The article concludes that attempting to change the world of Big Tech only using the technologies and tools they provide will at times prove to be counter-productive, and that political and other more disruptive avenues of action should also be seriously considered by ethicists who want to effect long-term change. Both strategies have advantages and disadvantages, and a combination might be desirable to achieve these advantages and mitigate some of the disadvantages discussed.

This article discusses the political economy of AI capitalism. It considers AI as a General Purpose Technology (GPT) and argues we need to investigate the power concentration of Big Tech. AI capitalism is characterised by the commodification of data, data extraction and a concentration in hiring of AI talent and compute capacity. This is behind Big Tech's unstoppable drive for growth, which leads to monopolisation and enclosure under the winner takes all principle. If we consider AI as a GPT – technologies that alter society's economic and social structures – we need to come up with alternatives in terms of ownership and governance. The commons is proposed as an alternative for thinking about how to organise AI development and how to distribute the value that can be derived from it. Using the commons framework is also a way of giving society a more prominent role in the debate about what we expect from AI and how we should approach it.

This article discusses the political economy of AI capitalism. It considers AI as a General Purpose Technology (GPT) and argues we need to investigate the power concentration of Big Tech. AI capitalism is characterised by the commodification of data, data extraction and a concentration in hiring of AI talent and compute capacity. This is behind Big Tech's unstoppable drive for growth, which leads to monopolisation and enclosure under the winner takes all principle. If we consider AI as a GPT—technologies that alter society's economic and social structures—we need to come up with alternatives in terms of ownership and governance. The commons is proposed as an alternative for thinking about how to organise AI development and how to distribute the value that can be derived from it. Using the commons framework is also a way of giving society a more prominent role in the debate about what we expect from AI and how we should approach it.