Review of the Artificial Intelligence Industry Reveals Challenges

“Care is not a problem to be solved; it is a fundamental part of living as humans,” said Fay Niker, a philosophy lecturer at the University of Stirling, and chair of the Coding Caring workshop. “The idea of a technical fix for something like loneliness, for example, is baffling.”

The workshop participants frame care technologies as tools to supplement human care relationships like those between a caregiver and care-receiver. Technology can certainly give reminders to take medication or track health information, but is limited in the ability to display empathy or provide emotional support which cannot be commodified or reduced into outcome-oriented tasks.

“We worry that meaningful human interaction could be frozen out by tech,” said Niker. “The hope is that the AI2020 report, and other work in this area, will contribute to preventing this ‘ice age’ by challenging and hence changing the culture and debate around the design and implementation of caring technologies in our societies.”

Regulating Predictive Technologies
AI technologies may be capable of learning, but they are not immune to becoming outdated, prompting participants in the second workshop to introduce the concept of “expiration dates” to govern their deployment over time. “They train on data from the past to predict the future,” said Altman. “Things change in any field, so you need to do an update or a reevaluation.”

“It means we have to pay attention to the new data,” said David Robinson, a visiting scientist from Cornell’s College of Computing and Information Science, and one of the workshop organizers. Unless otherwise informed, the algorithm will blindly assume that the world has not changed, and will provide results without integrating newly introduced factors.

Important decisions can hinge on these technologies, including risk assessment in the criminal justice system and screenings by child protection services. But Robinson stressed that it is the net combination of the algorithm results and the interpretation from those using the technology that results in a final decision. There should be as much scrutiny on the information that the AI is providing as there is on the users who are interpreting the algorithm’s results.

Both workshops came to the conclusion that regulation is needed for AI technology, according to Altman, which should come as no surprise to those attuned to popular culture references of the field. Whether the industry can self-regulate, or what other entities should oversee the progress in the field, is still in question.

Participants and organizers alike feel that the AI100 has a role to play in the future of AI technologies. “I hope that it really helps educate people and the general public on how they can and should interact with AI,” said Stone. Perhaps even more importantly, the outcomes from the AI reports can be referenced by those policymakers and industry insiders, shaping how these technologies are developed.