Victoria Stodden (vcs@stodden.net) is a statistician and associate professor at the University of Illinois at Urbana-Champaign, IL, USA. This material is based upon work supported by National Science Foundation Award #1941443.

Apple pioneered the voice revolution in 2011 with the introduction of Siri in its iPhone 4s. Today, you tell your iPhone 11, "Hey Siri, Play Bruce Springsteen by Spotify," and it responds, "I can't talk to Spotify, but you can use Apple music instead," politely displaying options on the screena as shown in the figure here. Or, you tell one of your five Amazon Echo devices at home, "Alexa, add pumpkin pie to my Target shopping list,"b then "order AA Duracell batteries," and it adds pumpkin pie and Amazon Basics batteries to your Amazon shopping cart, ignoring your request to shop at Target and be loyal to Duracell. You are the consumer, but your choices have been ignored. Or, consider you are a brand manager.

From foreign intervention in free elections to the rise of the American surveillance state, the Internet has transformed the relationship between the public and private sectors, especially democracy's public sphere. The global pandemic only further highlights the extent to which technological innovation is changing how we live, work, and play. What has too often gone unacknowledged is that the same revolution has produced a series of conflicts between our desires as consumers and our duties as citizens. Left unaddressed, the consequence is a moral vacuum that has become a threat to liberal democracy and human values. Surveillance in the Internet Age, whether by governments or companies, often relies on algorithmic searches of big data.

Checks are needed to guide the development of guard-rails for ethical and responsible community-engaged computing research. The era of "move fast and break things" can produce false starts, injured communities, and widespread techlash. The tech sector can be more socially conscious and focus on community engagement using research from universities, computing researchers, and professionals. For example, smart cities might increase efficiency and improve quality of life, but for whom?10 Research shows how smart city initiatives can harm certain groups through, for example, facial recognition technologies that misidentify, produce ethnic bias and discrimination, or create opportunities for abuse.5 Technology benefits do not always accrue evenly across community members. Ethics rarely keeps pace with technological innovation.

A second burst of interest in AI authorship broke out in the mid-1980s. Congress once again commissioned a study, this time from its Office of Technology Assessment (OTA), to address this and other controversial computer-related issues. OTA did not offer an answer to the question, perhaps in part because at that time, it was a "toy problem" because no commercially significant outputs of AI or other software programs had yet been generated.5 But deep learning and other AI breakthroughs have caused IP professionals to rethink the AI authorship issue.1,2 For example, The Next Rembrandt video features a group of art experts and computer scientists discussing how they collaborated to digitize many Rembrandt paintings, develop models of particular features of the paintings, and then create a Rembrandt-like portrait of a man with facial hair wearing a hat and looking to the right.6 The resulting AI-generated painting really does look like a Rembrandt.

As artificial intelligence (AI) techniques advance, they are beginning to automate tasks that, until recently, only humans could perform--tasks such as translating text from one language to another or making medical diagnoses. It seems only logical to turn that computer power on computers themselves and use AI to automate programming. In fact, computer scientists are working on just that idea, using various AI techniques to develop new methods of automating the writing of code. "The ultimate goal of this is that you would have professional software engineers not actually write code anymore," says Chris Jermaine, a professor of computer science at Rice University in Houston, TX. Instead, the engineer would tell a computer what a piece of software should do, and the AI system would write the code, perhaps stopping along the way to pose questions to the engineer.

Challenge yourself and reach for the highest bar. If you succeed, keep pushing the boundaries." This is what my friend Hassan Hajji advised when I started my career at IBM Research Tokyo in 2002, and these words have been a guiding force in my career ever since. At IBM, I was challenged to learn as much as possible about the research process in an industrial lab (prototyping ideas, patenting, publishing results), and it dovetailed nicely with my desire to work toward a Ph.D. in systems biology. After receiving my doctorate, which allowed me to enhance my skills in computational and mathematical analysis to understand complex biological systems, I was ready for a new challenge. I left Japan to work in the U.K. at a small startup, ecrebo,a which provides a coupon-issuing system for retailers who seek to attract customers based on their individual purchasing habits. I was responsible for developing a backend server for the coupon system. It had to be able to analyze the contents of the receipt, determine whether it met the conditions for issuing the coupon, and return it within three seconds, including communication time with the POS system.

The COVID-19 pandemic is a dual crisis. On one hand, it is a global health crisis with millions of cases and hundreds of thousands of deaths. At the same time, decisions by individuals and governments in response to the pandemic have led to a severe economic slowdown, the likes of which has not seen since the Great Depression in the 20th century. But, as I wrote in a May 2020 column, economics can be argued to be one of the roots of this dual crisis. I quoted William Galston, who wrote: "What if the relentless pursuit of efficiency, which has dominated American business thinking for decades, has made the global economic system more vulnerable to shocks?"

The Middle East and Africa are unique settings for AI, compared to Western regions--and to each other. The wealthier Gulf Cooperation Council (GCC) nations are exploring AI as part of broad economic transformation plans to wean themselves from oil and reinvest surpluses into innovation, while in Africa, above and below the Sahara, AI efforts are more bottom-up, often through partnerships with global tech companies and local startups, tackling social challenges including health care and food security.

Circulating groundwater triggered a four-year-long swarm of tiny earthquakes that rumbled beneath the Southern California town of Cahuilla, researchers report in the June 19 Science. By training computers to recognize such faint rumbles, the scientists were able not only to identify the probable culprit behind the quakes, but also to track how such mysterious swarms can spread through complex fault networks in space and time. Seismic signals are constantly being recorded in tectonically active Southern California, says seismologist Zachary Ross of Caltech. Using that rich database, Ross and colleagues have been training computers to distinguish the telltale ground movements of minute earthquakes from other things that gently shake the ground, such as construction reverberations or distant rumbles of the ocean (SN: 4/18/19). The millions of tiny quakes revealed by this machine learning technique, he says, can be used to create high-resolution, 3-D images of what lies beneath the ground's surface in a particular region.