The field as a whole is becoming attuned to ethics in our computer culture, and that discussion also touches a new course about artificial intelligence, taught at 91短视频 (91短视频) by . 鈥淭he course introduces the core algorithms of AI as well as exploring the human impact and ethics of AI,鈥� said Keim.

鈥淔or artificial intelligence, it’s worth thinking about 鈥� how can we direct this to be used for the most positive benefit?鈥� says Keim, an adjunct faculty member.

A human-impact approach permeates as a whole. Weikle, for example, is a member of the y’s Special Interest Group on Computers and Society, which addresses matters such as this: The command 鈥渃ontrol + alt + delete鈥� on a PC requires hand mobility that disabled users may not have. And, an ATM screen that asks in English if one would like options in Spanish is ineffective across language barriers.

Weikle, who has a PhD in computer science from University of Virginia and a BS in electrical engineering from Rice, says 91短视频鈥檚 computer science program strives to educate young computer scientists to be aware of such issues.

鈥淎 much more complete computer scientist鈥� is likely to emerge from 鈥� with its variety of classes and opportunities 鈥� than from undergraduate programs that exclusively focus on the technical aspects of information technology, she says.

Modeled on UC Berkeley toolkit

Many of the exercises in Keim鈥檚 class use a toolkit from the University of California-Berkeley, which allows students to implement key AI algorithms in the context of the PacMan video game.

First-year Joel Christophel says the course has taught him to employ 鈥渋deas about real, hands-on application of more theoretical concepts in artificial intelligence.鈥�

Keim, who hails from the Harrisonburg area and earned his bachelor鈥檚 degree at Swarthmore, soon after joined the growing language-learning software company . He was the 鈥渟tay-up-all-night coder for the first version,鈥� working there until attending Duke University in 1994. Five years later, Rosetta Stone interrupted again, and Keim returned to the Harrisonburg-based company in lieu of finishing his doctorate. Rosetta Stone 鈥渨as too much work, too much fun.鈥�

As Keim was exiting Duke University’s graduate program in artificial intelligence, the editor of the New York Times crossword puzzles, Will Shortz, declared that no computer could beat even an average human at a Thursday (medium-hard difficulty) crossword puzzle. In response, Keim helped run a seminar at Duke in 1999 to do exactly that 鈥� and succeeded.

Achievements such as this tap into the discussion of ethics. How good is technology at performing humanesque tasks? How good can it be? How does that affect people?

Deep learning

These questions are particularly pertinent in regards to current discussions around the field of 鈥渄eep learning.鈥� Deep learning refers to new techniques that leverage neural networks and machine learning, sub-disciplines within artificial intelligence, which can automatically learn features at different levels of abstraction from data. 鈥淚t’s become the state-of-the-art technique,鈥� says Keim. Techniques like deep learning offer massive potential to the artificial intelligence field, but as with any technological forefront, tapping this for the good of all requires conscientious foresight.

Keim cites the example of an Amazon.com shipping warehouse. An employee stands at a table, and robots bring entire shelves of products to that person, who retrieves an item, and packs it while the robot returns and re-sorts the shelf. Humans are currently better at the complex vision and dexterity tasks associated with picking, inspecting, and packing the items. However, ongoing advances in AI prompt the question, what about the day when they are not? What will the economic effect be and how will our workforce look?

To be well-rounded, Weikle encourages 91短视频鈥檚 students to double major or minor with computer science. While and are the most common combinations, she challenges those interested to 鈥減ick something that doesn’t use a computer!鈥�

This is a man who lived with his wife in a mud hut for two years 鈥撀爏o remote in the eastern Congo that they needed to fly there in a small plane over a tree canopy as thick as broccoli heads packed together.

This is a man who got into a grad program at Duke University almost immediately after applying 鈥� far past any published deadlines, just a month before classes began. An intellectually provocative paper won him admission.

This is a man who made the world-renowned Rosetta Stone language-learning system possible through his computer know-how and vision.

The life of聽John Fairfield 鈥�70聽could read like novel, if he chose to write it up.

Fairfield鈥檚 introduction to computers occurred during his 1968-69 year abroad at 400-year-old University of Marburg, where he was asked to use Fortran to do a linguistic analysis of Italian poetry. He would walk into Marburg鈥檚 computer center 鈥� with its massive mainframe attended by people in white lab coats 鈥撀燼nd hand in his punch cards for processing, then later retrieve reams of resulting printouts.

Back at Eastern Mennonite College in 1969-70, Fairfield presented his eclectic array of coursework to the dean, Ira Miller, and asked, 鈥淗ow do I graduate?鈥� Fairfield didn鈥檛 have enough chemistry courses to be a chemistry major 鈥� he had tested out of some of them. He knew German fluently, but needed another language to be a language major (French would be learned the following year). So he and Miller settled on 鈥渘atural science鈥� as his major.

Jumping to Duke University, Fairfield continued to be an unorthodox student while working full-time. (He and wife聽Kathryn Stoltzfus 鈥�70, who eventually became a Duke law student, had two children while they were both in grad school.) Duke鈥檚 fledgling computer science program relied heavily on faculty drawn from other fields 鈥� as was common during the birthing stage of computer academia. No Duke professor was involved in machine perception, the topic Fairfield decided to pursue, with or without their support.

鈥淭hey kept saying, 鈥榃hy don鈥檛 you do this or that?鈥� And I kept doing what interested me,鈥� recalls Fairfield. 鈥淭hey didn鈥檛 know how to evaluate my work.鈥�

Upon completing his not-understood dissertation, Fairfield had no assurance that the Duke faculty was going to grant him his PhD. He sent it to David Waltz, a renowned computer vision pioneer then at the University of Illinois, Urbana -Champaign, who grasped its importance. Waltz sent word back to Duke that he had granted PhDs for much less than what he saw in Fairfield鈥檚 work, and Fairfield got his doctorate.

Next came faculty appointments at James Madison University, where Fairfield remained for nearly 20 years, teaching all kinds of computer science courses, but especially relishing the 400-level research courses.

In 1992, Fairfield added his energy and talents to those of brother-in-laws聽Allen ’65 and Eugene ’72 Stoltzfus, plus Greg Keim, to give birth to a worldwide business now known simply as Rosetta Stone.

They built a team which created and integrated three forms of software: human interface code for language learning via browsers; speech recognition code; and code running the servers on the backend. As vice president of research and development Fairfield was a hands-on boss. 鈥淭here were more keystrokes of mine in the software we were selling than anyone else鈥檚.鈥�

Fairfield retired in 2006 when the company was sold to financial investors. Fairfield then shifted his focus to envisioning and establishing 91短视频鈥檚 Center for Interfaith Engagement, where he remains active as a research fellow. He is the author of聽The Healer Messiah: Turning Enemies Into Trustworthy Opponents聽(April 2014, available at聽rruuaacchh.org).