The AI Con
How to Fight Big Tech’s Hype and Create the Future We Want
Emily M. Bender and Alex Hanna
Having read it
★★★★★
Very, very realistic, sensible and good and definitely a productive assistant to understanding, learning and adapting one’s resistance to the AI hype.
Let us be clear: we are not anti-technology, not even technology that involves the kind of pattern-matching algorithms used in ‘Al’ systems. But we want to see technology that is designed with an understanding of both the needs and values of the people using it and of those it might be used on. In other words, we want technology that is created to strengthen and empower communities, not technology that reproduces and enables systems of oppression, consolidation of power, and environmental devastation.
A good passage
AI hype reduces the human condition to one of computability, quantification, and rationality. If we are just organic versions of computing machines, then we should interact with these software systems as if they were silicon-based life-forms, whether friends or foe. In this line of argumentation, humans can be reduced to our outputs and the ways in which we interact with our environment, with people, and with written and visual production. If we accept that, consciousness can be judged by how it manifests in phenomena that are external to the mind.
Viewing humans as a kind of machine has far-reaching implications for the field of computing and how Al is hyped up in broader circles. [Joseph] Weizenbaum [German-American computer scientist and professor at the Massachusetts Institute of Technology] pushed against this framing of the human. As tech writer and cofounder of Logic Magazine Ben Tarnoff wrote in a recent Guardian profile, Weizenbaum believed that
computers constricted rather than enlarged our humanity, prompting people to think of themselves as little more than machines. By ceding so many decisions to computers . . . we had created a world that was more unequal and less rational, in which the richness of human reason had been flattened into the senseless routines of code.
A second good passage
All of them [government leaders who have accepted generative AI into the work and operations of government with confidence and enthusiasm] use words such as ‘ethical’, ‘responsible’, and the like, but there could be another option: just don’t use these tools. Government processes that affect people’s liberty, health, and livelihoods require human attention and accountability. People are far from perfect, subject to bias and exhaustion, frustration, and limited hours. However, shunting consequential tasks to black-box machines trained on always-biased historical data is not a viable solution for any kind of just and accountable outcome.
A third good passage
Shifting away from ‘innovation’ towards regulation that protects people makes it clear that it’s not the details of the technology that should be the focus, but its potential to impact people and society. In other words, the expertise needed to effectively regulate technology is expertise in sociotechnical systems, human and civil rights, and the crafting of laws such that they achieve the desired goals. While tech companies would like policymakers to feel snowed under by progress and to think they are perpetually playing catch-up, policymakers should be concerned with protecting rights and maintaining civic structures, things that don’t change so fast.
We call on policymakers to look into the ways in which both the production and use of the new technology are trampling on human and civil rights and ask: how can those rights be better protected and what regulatory and enforcement mechanisms would be effective in protecting them?