How to make AI that’s good for people
The Future of Artificial Intelligence: A Human-Centered Approach
As artificial intelligence (AI) continues to revolutionize industries and transform the way we live and work, it's essential to consider the impact of this technology on society. Despite its name, AI is not an "artificial" entity; it's a creation of humans, intended to behave like humans, and affects humans. Therefore, if we want AI to play a positive role in tomorrow's world, it must be guided by human concerns.
A Human-Centered Approach to AI
I propose a human-centered approach to AI, which consists of three goals that can help responsibly guide the development of intelligent machines.
Goal 1: Reflecting Human Intelligence
AI needs to reflect more of the depth that characterizes our own intelligence. Human visual perception, for example, is complex and deeply contextual, balancing our awareness of the obvious with a sensitivity to nuance. By comparison, machine perception remains strikingly narrow.
Consider the example of an image-captioning algorithm that fairly summarized a photo as "a man riding a horse" but failed to note the fact that both were bronze sculptures. This difference may seem trivial, but it points to a major aspect of human perception beyond the grasp of our algorithms. How can we expect machines to anticipate our needs—much less contribute to our well-being—without insight into these "fuzzier" dimensions of our experience?
Goal 2: Enhancing Humans, Not Replacing Them
Making AI more sensitive to the full scope of human thought is no simple task. The solutions are likely to require insights derived from fields beyond computer science, which means programmers will have to learn to collaborate more often with experts in other domains.
Such collaboration would represent a return to the roots of our field, not a departure from it. Younger AI enthusiasts may be surprised to learn that the principles of today's deep-learning algorithms stretch back more than 60 years to the neuroscientific researchers David Hubel and Torsten Wiesel, who discovered how the hierarchy of neurons in a cat's visual cortex responds to stimuli.
Reconnecting AI with fields like cognitive science, psychology, and even sociology will give us a far richer foundation on which to base the development of machine intelligence. And we can expect the resulting technology to collaborate and communicate more naturally, which will help us approach the second goal of human-centered AI: enhancing us, not replacing us.
Imagine the role that AI might play during surgery. The goal need not be to automate the process entirely. Instead, a combination of smart software and specialized hardware could help surgeons focus on their strengths—traits like dexterity and adaptability—while keeping tabs on more mundane tasks and protecting against human error, fatigue, and distraction.
Or consider senior care. Robots may never be the ideal custodians of the elderly, but intelligent sensors are already showing promise in helping human caretakers focus more on their relationships with those they provide care for by automatically monitoring drug dosages and going through safety checklists.
Goal 3: Ensuring AI Benefits Humans
No amount of ingenuity, however, will fully eliminate the threat of job displacement. Addressing this concern is the third goal of human-centered AI: ensuring that the development of this technology is guided, at each step, by concern for its effect on humans.
Today's anxieties over labor are just the start. Additional pitfalls include bias against underrepresented communities in machine learning, the tension between AI's appetite for data and the privacy rights of individuals, and the geopolitical implications of a global intelligence race.
Adequately facing these challenges will require commitments from many of our largest institutions. Universities are uniquely positioned to foster connections between computer science and traditionally unrelated departments like the social sciences and even humanities, through interdisciplinary projects, courses, and seminars. Governments can make a greater effort to encourage computer science education, especially among young girls, racial minorities, and other groups whose perspectives have been underrepresented in AI. And corporations should combine their aggressive investment in intelligent algorithms with ethical AI policies that temper ambition with responsibility.
The Future of AI: A Human-Centered Approach
No technology is more reflective of its creators than AI. It has been said that there are no "machine" values at all, in fact; machine values are human values. A human-centered approach to AI means these machines don't have to be our competitors, but partners in securing our well-being. However autonomous our technology becomes, its impact on the world—for better or worse—will always be our responsibility.
As we move forward with AI, it's essential to prioritize human-centered design, ensuring that this technology serves humanity's needs and values. By doing so, we can create a future where AI enhances our lives, rather than controlling them. The future of AI is not just about machines; it's about people, and the values we choose to uphold.
Source: https://blog.google/innovation-and-ai/technology/ai/how-make-ai-good-for-people/
