Popular discourse on Artificial Intelligence (AI) resembles the parable of the blind men and the elephant. This story recounts the disparate understandings that emerge from the limited experiences of each individual blind man encountering a different part of the elephant - tusk, side, leg, trunk, ear, and tail. AI has permeated much of our technology-augmented work, but like the blind sojourners, we may each have different ideas about what it is and, by inference, what it is not.
The emergence of this new technology raises questions concerning whether the pace of technological innovation has outpaced the law. For instance, US law currently only recognizes humans as creators. It also grants intellectual property (IP) rights only to persons, natural or corporate, regardless of their reliance on AI.
With AI we can get predictions that we can not explain but that we can not match or surpass. Some of these predictions are valuable, but some are flawed due to defects in the training data. Who or what we hold accountable for these flaws, and what incentives we do or do not create for their correction will influence AI’s hand in how we work.
In our series of podcasts, we hope you will join us as we work to refine, sharpen, and clarify the layperson’s understanding of what AI is, what it can do well, and what it cannot do well. We will also explore how some of AI’s limitations grow out of overambitious application and bad data. These are the kinds of gaps we invite you to explore with us and our guest speakers.