A new wave of AI is being explored currently, which adds humans to the equation as positive influencers of events rather than passive recipients, thereby creating new possibilities for the future.
In recent popular imagination, there have been only two common (mis)understandings of AI. It is either the great saviour, which will automate all the jobs that humans shouldn’t be doing in the first place. Or, it is a sign of destruction, full of foreboding, entering into the ecosystem of humans with the aim to displace them from it. These understandings are rooted in and portrayed through various fictitious mediums; those who are within the field of AI and ML understand the reality is far from either of two situations - with the recent progress in GTP-3 being the only remarkable thing to straddle both imaginations, and rather ineffectively at that.
With that said, however, there is a new wave of AI being explored currently, which falls in neither of the two visions. Instead of being centered completely around AI, this vision imagines AI as a collaborative effort with humans, and therefore forces us to rethink the inherent possibilities of such a partnership. By adding humans to the equation as positive influencers of events rather than passive recipients, this partnership makes us reimagine the potential of a future that is neither dystopian nor utopian.
This leads us to the question: what are some ways in which this partnership has already been explored? And how is it likely to be explored in the future?
Exploring the Possibility of a Human-AI Partnership
As far back as 2017, Daniela Ras, in a Keynote speech at MIT, spoke of a project in which AI helps vision-impaired commuters navigate through self-driving cars. Her brave quote was this: “I believe people and machines should not be competitors, they should be collaborators.” And it’s not just at MIT that this noble idea was explored - it has also been explored in another part of the world, at Amsterdam, where AI has been used in the process of manufacturing steel, helping identify faults in the various stages of the manufacturing process. These faults then get verified by human experts, with the overall setup constituting another scenario of successful collaboration between humans and AI.
One of the most remarkable instances of AI outsmarting humans had been in the field of chess. When the IBM Computer Deep Blue beat Garry Kasparov in 1997, it ruffled the feathers of all in both the emerging computing industry as well as those in chess. Two decades on, there is a new form of chess - Centaur Chess - which teams up a human and AI against humans or AI or a combination of the two. This new revolutionary form of chess teams up the emotive capacities of humans with the data-crunching capacity of computers, and the results are explosive.
Understanding the Human-AI Relationship in Depth
As the human-ai relationship is explored in different areas through different collaborations, more and more data will be required on how to fit this into the structure of work. For instance, AI is assisting and collaborating with a human workforce in hundreds of different fields right now - in some places as an extension of the human body, while in other places as expert fraud detection mechanisms.
Much work is still to be done in this domain - and the future is anybody’s bet at this point. To further this understanding, Prof. Phanish Puranam of INSEAD is conducting an online survey here, which seeks to illuminate various aspects of a developing consciousness towards AI. This includes the preferred collaboration style when it comes to working with AI, as well as level of trust in multiple collaboration configurations with AI, and aversion and/or acceptance of AI.
On completion, a one page downloadable “cheat sheet” of curated content (links to articles/videos) that will bring readers up to the cutting edge of thinking about how AI is affecting organizations.