Michael I. Jordan from the University of California, Berkeley, recently wrote an article for Medium called “Artificial Intelligence – The Revolution Hasn’t Happened Yet.”
Computing Research News
Many recent symposia and workshops have highlighted both the progress and opportunities for AI and its potential to contribute to new products, services, and experiences. However, we should not lose sight of the fact that fielding real-world systems that realize these innovations will also drive significant advances in virtually all areas of computing, including areas that are not traditionally recognized as being important to AI research and development. To highlight these synergies, the CCC AI and Robotics Task Force released a white paper for the community.
The past year has seen an incredible amount of ink spilled on a singular topic: what does the future of AI portend for the nation and the world? Will AI technologies enhance productivity and quality of life, or will it disrupt labor markets and accelerate growth in income disparity and wealth concentration? Will AI research be used for the common good, or will it be “bought up” by the private sector and exploited for commercial gain? Is this another AI research bubble, or are we truly on the verge of a paradigm shift that could change the nature of computing itself?
In a recent blog post, we summarized the report of an academic/industry roundtable, which, among other recommendations, advocated for mechanisms to support long-term, strategic, and sustained conversation between academics and industry representatives. Recently, one such mechanism came into being with the announcement of the Partnership on AI by a consortium consisting of Microsoft, Google, Amazon, Facebook, and IBM.
What do you think your field will look like in 100 years? Speculating about the world a century from now may be too challenging, so what if instead a community took it upon itself to periodically assess its progress and potential nearer-term futures over time? How might such reflections influence the rate of progress, the types of problems that the field focuses on, the public perception of the work, or the ability to anticipate and address thorny ethical or policy questions?
The first step on a project to answer these questions was taken with the release of the first report of the One Hundred Year Study on Artificial Intelligence (AI100).