Posts
 |
| Looking at a multi-disciplinary future for AI Photo: National Energy Scientific Computing Center |
That's why some leading voices in the academic and computer science community are calling for a new way of studying and understanding AI actions, which they call "machine behavior."
In a recent post, I explored current-day drivers of AI, which include gamers, hipsters and angels, who have applied the technology in highly unexpected ways. So, already, there are new forces at work bringing AI into the mainstream of business and society. In addition, C-level executives have increasing responsibility for the actions and behaviors of their AI-driven systems.
The academic community recognizes that AI has left the computer science building, metaphorically speaking. "Currently, the scientists who most commonly study the behaviour of machines are the computer scientists, roboticists and engineers who have created the machines in the first place. These scientists may be expert mathematicians and engineers; however, they are typically not trained behaviorists," writes Iyad Rahwan, who leads the Scalable Cooperation group at the MIT Media Lab, along with a wide team of computer and data scientists from leading universities. "They rarely receive formal instruction on experimental methodology, population-based statistics and sampling paradigms, or observational causal inference, let alone neuroscience, collective behavior or social theory." In their report, published in Nature, Rahwan's team proposes to increase this level of understanding by expanding the horizons of computer science into biology, economics, psychology, and other behavioral and social sciences.
Read more...
Source: Forbes
