A couple of weeks ago the MIT Media Lab presented the AHA project (Advancing Humans with AI), a research program that brings together 14 research groups from the prestigious university around the question "How can we design artificial intelligence in the service of human flourishing and fulfilling lives?" Amidst the corporate festival of generative AI models, it is encouraging to see how research projects are proliferating to understand how interaction with AI is modifying behaviors, expectations, and imaginaries.
The fact that we can talk to a chatbot as if it were a person has allowed these interfaces to become part of many everyday lives as conversational companions, assistants, or oracles. Far beyond professional uses to delegate routine tasks to them, what has grown the most in the last year is the emotional support, with special emphasis on combating loneliness.
Although most of the funding for innovation and AI comes from private fundsIn the academic field, there are also great efforts to measure and analyze the implications that are being unleashed. The MIT AHA project we mentioned earlier is a great example of research to inspire AI professionals in any field and to help them escape the narrative of efficiency and productivity. One of the lines of work is precisely to offer indicators to measure how AI brings us closer to or further away from inner, social, vocational, and creative vital fulfillment.
Projects like this—but also all previous efforts to promote AI that is in line with fundamental human rights and aligned with ethical principles and social justice—are essential for the negotiation phase we are in. It is worth noting that the most provocative initiatives are found at the intersection of art and research, bringing to light latent issues, expressing them visually and supported by method and evidence. An area in which the presence of women is also notable.
According to States of knowledge., edited by Sheila Jasanoff, science is the fruit of a shared production that goes through three phases: emergence, contestation, and stabilization. If we extrapolate these phases to the adoption of technologies, in the case of generative artificial intelligence, everything points to the fact that we are fully in the contestation phase: it has deployed rapidly and is being integrated into multiple fields, but there is still no social consensus on how, for what purpose, and within what limits it should be used.
In this phase, it is essential to have evidence and indicators, because we still have time to collectively decide what role we want AI to play in our lives. It is now that we can deliberate on which tools deserve our trust and what uses we consider acceptable and, above all, amidst the algorithms, codes, and data, continue searching for fuller lives and connections that sustain and nourish us.
