Contributed by Ron Baecker, an Emeritus Professor of Computer Science at the University of Toronto, co-author of The COVID-19 Solutions Guide and author of Computers and Society: Modern Perspectives (OUP, 2019).
My family is widely separated. I live in Canada. My brother-in-law, niece, nephew, and their families are in New Jersey and Pennsylvania; my cousins, their children, and their families are in Argentina, Spain, England, and on both coasts of the USA. Typically, I visit my niece and nephew once or twice a year; I manage a trip to Buenos Aires or Bilbao, Spain, about every 3 years. But not recently. I therefore Facetime with either my nephew or my niece almost every week. We also are about to have our fourth global family Zoom. This started out to celebrate individual birthdays, with great spirit and feeling of bringing the family closer together. The next event will celebrate 3 birthdays — ages 78, 41, and 9 — and a recent birth in the family in London. The 9-year-old birthday event will see us participating in a day-long scavenger hunt. What fun!
ContributedJudith A. Langer, who is a Distinguished Professor Emeritus of Education, a researcher who has specialized in language, literacy, and learning, and one of the co-authors of The COVID-19 Solutions Guide.
August and early September of 2020 were extremely difficult times for everyone who had a stake in education: parents, teachers, school administrators and local officials. In June and July, most people hoped school could resume in the ways it always had and this, I think, may have held them back from creating a fully planned “new normal.” Many early scenarios contained some online teaching in the event that in the future schools might need to be shuttered for periods of time, but they were hoping an overall easing of cases would permit in-class instruction. Most models contained scenarios for all in-class, hybrid and fully on-line to cover the unknown range of needs, but many did not. Unexpected spikes in Covid-19 in heretofore low-case regions escalated uncertainty about what the future might hold. Sizable ranges in the intensity of new cases within states and communities pointed to the need for more locally determined options.
A forecasting model is a prediction of how the world will evolve, of what will happen in the future with respect to some phenomena (such as the motion of objects, the financial health of a business) or the spread of an epidemic.
Contributed by Ronald Baecker, who is an Emeritus Professor of Computer Science at the University of Toronto, co-author of The COVID-19 Solutions Guide and author of Computers and Society: Modern Perspectives (OUP, 2019).
Readers of my blog will recall what I describe as digital dreams and digital nightmares.
Our world has been enriched by digital technologies used for collaboration, learning, health, politics, and commerce. Digital pioneers imagined giving humanity greater control over the universe; augmenting knowledge and creativity; replacing difficult and dangerous physical labour with robot efforts; improving our life span with computationally supported medicine; supporting free speech with enhanced internet reason and dialogue; and developing innovative, convenient, and ideally safe products and services. Online apps and resources are proving very valuable, even essential, in the era of COVID-19.
In this column, in my textbook, and in a speech “What Society Must Require from AI” I am currently giving around the world, I document some of the hype, exaggerated claims, and unrealistic predictions that workers in the field of artificial intelligence (AI) have been making for over 50 years. Here are some examples. Herb Simon, an AI pioneer at Carnegie-Mellon University (CMU), who later won a Novel Prize in Economics, predicted in 1958 that a program would be the world’s best champion by 1967. Marvin Minsky of MIT, and Ray Kurzweil, both AI pioneers, made absurd predictions (in 1967 and 2005) that AI would achieve general human intelligence by 1980 and by 2045. John Anderson, discussed below, made the absurd prediction in 1985 that it was already feasible to build computer systems “as effective as intelligent human tutors”. IBM has recently made numerous false claims about the effectiveness of its Watson technology for domains as diverse as customer support, tax filing, and oncology.
There is still time to buy a substantive book for the thoughtful techie or concerned citizen in your life. Allow me to recommend two choices that were published in 2019. One good option is my wide-ranging textbook Computers and Society: Modern Perspectives, enough said …. But an unbiased choice is Shoshana Zuboff’s monumental The Age of Surveillance Capitalism. The author signals her intentions with the book’s subtitle: The Fight for a Human Future at the New Frontier of Power.
Zuboff, the Charles Edward Wilson Professor Emerita, Harvard Business School, defines and describes surveillance capitalism (p. 8):
Every Computer Science student should get significant exposure to the social, political, legal, and ethical issues raised by the accelerating progress in the development and use of digital technologies.
The standard approach is to offer one undergraduate course, typically called Computers and Society or Computer Ethics. I have done this during the current term at Columbia University, using my new textbook, Computers and Society: Modern Perspectives (OUP, 2019). We meet twice a week for 75 minutes. In class, I present key topics covered in the book, and welcome a number of guest speakers who present their own experiences and points of view. Every class is interactive, as I try to get the students to express their own ideas. There have been four assignments: a policy brief, a book report, a debate, and a research paper. Such courses are typically not required by major research universities, which is a mistake, but they are often required by liberal arts colleges.
Contributed by Muriam Fancy. Muriam is a masters student at the Munk School of Global Affairs and Public Policy. She recently completed her BA in Peace, Conflict, and Justice with a double minor in Indigenous Studies; Diaspora & Transnational Studies. She runs Diverse Innovations (@diverseinnovat1), a platform discussing social good technology.
Amazon launched an artificial intelligence (“AI”) system in efforts to revolutionize its recruitment strategy, and found that their AI program was discriminatory against women. A Chicago court implemented an AI system called COMPAS to do a predictive risk analysis of the chances offenders are to re-offend either by committing the same crime that they were charged for or committing a more significant offense. However, the AI system used discriminated against black defendants noting that they will most likely commit a more significant offense in comparison to white defendants – read more in Chapter 11 of Computers and Society: Modern Perspectives.
A session at the New Yorker Festival this past weekend discussing how history will judge Trump got me thinking again about media, tweeting, and Donald J. Trump.
Media play a huge role in politics. Here are some examples. In the medium of a large enclosed space filled with people, Adolf Hitler was able to whip crowds to a frenzy. Franklin Delano Roosevelt in his radio fireside chats reassured Americans that they could and would survive the economic hardships of the Great Depression. Winston Churchill’s stirring oratory during World War II lifted the spirits of people in Great Britain despite the Germans’ intense aerial bombardment. John F Kennedy‘s photogenic and relaxed television manner when contrasted with Richard Nixon’s swarthy scowling played a huge role in his victory in the 1960 US presidential election. Finally, Ronald Reagan’s commanding performances in televised addresses and his style of speaking to Americans in ways that they could understand and could trust justified his being called “the great communicator“.