AI is the Terminator. AI is coming for your job. AI is taking over the world. If we compiled all the headlines about artificial intelligence from the last year, we鈥檇 have a picture of a dystopian world where jobs are scarce and AI and automation rule everything we do. In this scenario, millions of people are impacted by AI and autonomous systems created with little regard for their consequences: They are deployed in unethical ways, riddled with errors and bias, and discriminatory. The obscurity of how AI works and where it鈥檚 used result in fear and confusion. And the few who still have jobs are far wealthier and more powerful than everyone else.
But there鈥檚 another story that doesn鈥檛 often get catchy headlines. Imagine a world where AI supports and improves our human capabilities. Algorithms and the data sets used to train them are open and transparent, giving users control and democratizing access. AI and automation work alongside humans to help teachers personalize curricula for students who learn in different ways, enable doctors to make more specific medical diagnoses, and give the elderly and people with disabilities mobility through assistive robotics. And forward-thinking and proactive policies address the potentially problematic effects these new technologies may have on our lives.
In this special collection of Commentary essays, professors, advocates, and futurists challenge us all to deeply consider how schooling must change鈥攁nd change soon鈥攖o meet the needs of a future we cannot yet envision.
This special section is supported by a grant from the . 澳门跑狗论坛 retained sole editorial control over the content of this package; the opinions expressed are the authors鈥� own, however.
This second future is not the path we鈥檙e on now鈥攁t least not yet. In order to get there, we need to take direct and urgent action collectively to address how AI is developed, tested, and deployed.
A relatively homogenous group of people are the current creators, researchers, and builders of AI. One consequence of this homogeneity is that AI systems unintentionally reflect or amplify unconscious societal biases. We see this already in racially biased risk-assessment software in prisons (which rate the likelihood of black people committing future crimes as higher than white people), language-translation software with gender bias (such as translating doctors as men and teachers as women), and face-recognition software that has trouble reading nonwhite faces. As we incorporate AI into our daily lives through health care, transportation, and financial and social services, opaque algorithms have the potential to perpetuate the power and wealth inequalities we already face.
This is precisely why AI consumers鈥攖hat means all of us鈥攎ust be involved in creating and shaping AI for the future. And that starts when we develop students鈥� interest and experience in AI at a young age. By bringing diverse experiences and viewpoints into software and project creation, we鈥檒l see more innovative and creative outputs that better meet the changing needs of our country. At this point, only about 40 percent of U.S. schools nationwide report offering computer science courses. African-American and Hispanic students made up only around 4 percent and 9 percent of test-takers in Advanced Placement computer science, respectively, in 2014. And girls make up only 27 percent of students who took computer science tests in 2017.
But education, mentorship, and outreach programs for underrepresented youths can make a big difference. At the San Francisco Bay Area-based organization AI4ALL (which I lead), we partner with AI labs at universities, such as Carnegie Mellon, Princeton, Stanford, and University of California, Berkeley, to introduce high school students to computer science concepts and skills. It only takes a few weeks of basic training before students are ready to apply concepts to humanitarian projects with help from professors. Some students have worked on projects to make hospitals safer using computer vision to identify hand germs, used natural-language processing on Twitter to find people in need of natural-disaster relief, and made driving safer and more accessible through designing autonomous cars.
Since the organization began in March, at least one-third of our more than 100 alumni have gone on to create their own AI programs in their communities, including teaching AI and computer science to middle schoolers from backgrounds traditionally underrepresented in STEM, running girls鈥� AI clubs, and hosting AI art workshops. Alumni of the program will also have access to ongoing support from peer and mentor networks as they continue their education and move into careers. For students of color and girls, having diverse mentors in the field plays an important role in showing them what is possible. Ours is not the only effort being made. Other education-based approaches鈥擟ode2040, the CSforAll Consortium, TEALS, and the College Board鈥檚 new AP computer science principles course鈥攁re also working to bridge gender and diversity gaps in coding and computer science through funding and after-school and summer programs.
There isn鈥檛 just one inevitable future for us. Making the latest developments in disruptive technology accessible to all is critical for taking control of our 21st-century lives. As Erik Brynjolfsson and Andrew McAfee write in The Second Machine Age, 鈥渢echnology is not destiny.鈥� Let鈥檚 not wait until AI鈥檚 problems become even more expensive and difficult to address. As educators, policymakers, technologists, and technology users, we can all play an active role in ensuring that a future full of artificial intelligence is actually intelligent. Let鈥檚 act while there鈥檚 still time.
