Computational Conscience

Since the onset of the COVID-19 pandemic, tech giants made a point to invest in research and development for next generation technology, with recent artificial intelligence (AI) innovations marking new reputes. For instance, OpenAI’s AI chatbot, ChatGPT, has seized media attention for its benchmark skills with apparent human-resembling communication yet super computer-wielding knowledge. However, the first impressions of the AI-as-normal world remain mixed. Even OpenAI’s CEO Sam Altman acknowledges that while post-ChatGPT AI could, at best, have possibilities better than he could imagine; it could—at worst, kill us all. That is quite the gap to close.

In recent weeks, global press has reported instances of surprising, racist, sexist, and disinformed responses and interactions with ChatGPT. On social media, the memes detailing these interactions have been nothing short of mystifying. Within a week of debuting in November 2022, ChatGPT gained one million users and after two months, 100 million users. This is a milestone for user participation with AI of this scale.

However, Silicon Valley was not alone behind the thrills of ChatGPT, reports detailed how OpenAI used outsourced Kenyan labourers, earning less than $2 per hour, to make ChatGPT less toxic by generating labelled examples for AI to detect and remove toxic language like violent, sexist and racist remarks. Workers in Kenya, Uganda, and India were exposed to text from the internet describing child sexual abuse, bestiality, murder, suicide, torture, self-harm, and incest. The firms employing these outsourced workers claim to have ‘lifted’ tens of thousands of people out of poverty.

Coupled with the immense climatological burden of sustaining the systems required for AI like ChatGPT—developed on 175 billion parameterized large language models (LLMs)—one thing is certain: immense expenses are necessary. The future of AI comes with costs not just to the environment, labour rights, or global equity but how the idea of freedom itself comes to be. This includes how emerging AI innovation is based on technology predicated on sustaining autocratic regimes, fascist interests, surveillance capitalism, data colonialism, and property rights. These information practices are hinged on commodifying our private data to create new social systems that remake the world in ways defined by the capital-seeking power-consolidating interests underlying these structures and those who enable them.

Recently, historic initiatives such as the Partnership on AI’s Responsible Practices for Synthetic Media, the European Union’s AI Act, and other government- and civil society-based guidelines and frameworks have been pursued to ensure that AIs are built responsibly. However, lawmakers struggle to keep up as the technological developments and technical details render some of these policies and controls already outdated by the time they are published.

These efforts are defined by theories of freedom shaped by Western historical interests—from colonialism to imperialism to corporatism—liberty is seen as either ‘compliance’ or ‘resistance’. We have yet to be able to conceive, plan, produce, and assess AI in a way that takes on robust ideas of freedom in mind. While practitioners, scholars, and activists have called for ‘AI ethics’ and even ‘algorithmic accountability’, what we really require is a better definition of freedom with AI that lead towards a ‘computational conscience’.

UNINTELLIGIBLE ETHICS AND ACCOUNTABILITY

In Romeo and Juliet, Shakespeare asked, ‘What’s in a name? That which we call a rose by any other name would smell as sweet.’ Today, those seeking to bridle AI confront a similar problem of names. What name affords better controls: ‘AI Ethics’ (AIE) or ‘algorithmic accountability’ (AA)?

Notions of ethics and accountability in technology are based on legacy concepts of what it means to be human, how human systems are propped on those concepts, and how those systems recreate structures that design and reiterate all features of human life.

These histories indicate that on their own, ethics and accountability contain incomplete concepts and accounts of liberty; the foundational value of human rights. Historians and social scientists have criticized how the premise of rationality underlying the definition of humanness in Western philosophy isn’t simply reductive but rather instigates the justification of violent and dehumanizing notions like enslavement, empire, and supremacy. Similarly, frameworks around what freedom and liberty look like and should be—both in practice and as ideals—share these roots.

The binary framing of thought as ‘logical’ and ‘illogical’ is uniquely Western. Defining these thoughts as complying with or defying logic follows suit. Western legal theories have historically framed ideas about freedom and liberty along the positions of acquisition or resistance. Similarly, Western ethics invokes a view of freedoms shaped by what philosopher Isaiah Berlin first described as positive liberty; ‘the freedom to,’ whereas accountability invokes negative liberty, ‘the freedom from.’

‘AI Ethics,’ positioned as the acquisition of AI via ethics, should be seen as a positive liberty framing of AI whereas ‘algorithmic accountability,’ the resistance to AI via accountability tools, should be seen as a negative liberty framing. As AIE and AA are based on liberty shaped by human nature, these terms lend limited accounts of what freedom and non-freedom is and could be. Understanding the full dynamics of AIE and AA requires a theory of freedoms beyond these reductive, binary legacy concepts to holistically integrate ethics and accountability into a new approach instead of reproducing historical knowledge limits—for better or worse.

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Computational Conscience

UNINTELLIGIBLE ETHICS AND ACCOUNTABILITY

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