Augmented intelligence vs. artificial intelligence

In the context of the central theme of the annual Workshop on Information Technology and Systems — to which I have the privilege of being the program co-chair this year — I want to share my thoughts on how academics and industry are reassessing the future role of intelligence.

By Raghu Santanam, Chair

Department of Information Systems

 

“…the main intellectual advances will be made by men and computers working together in intimate association.” — Joseph Carl Robnett (J.C.R) Licklider, 1960

In the context of the central theme of the annual Workshop on Information Technology and Systems (WITS 2017) — to which I have the privilege of being the program co-chair this year — I want to share my thoughts on how academics and industry are reassessing the future role of intelligence.              

While artificial intelligence, machine learning, and other autonomic technologies are usually in the spotlight, humans and computers solve many significant problems cooperatively. Thus, the design of information systems has to focus as much on intelligence augmentation (IA) as it does on artificial intelligence (AI). IA requires a focus on interaction design that optimizes the abilities of human analysts to direct the computational process. As such, designers of information systems have to increase their focus on interactions, control, and interface points such that the resulting system is efficient, effective, and addresses the issues of appropriate human control. Applications of augmented intelligence are beginning to emerge in some domains such as cybersecurity, counter-terrorism, and space exploration.

In the 1960s, Douglas Engelbart and Licklider (both managed research programs at the Defense Advanced Research Projects Agency) pioneered the arguments for human-computer symbiosis. A fundamental assumption behind the need for human-computer symbiosis is that computers and human brains have different problem-solving capabilities. As such, IA research pursues design ideas that are intended to optimize the combined computational potential of humans and machines. One branch of IA very familiar to information systems researchers is the human-computer interaction (HCI). One of the pioneers of the HCI approach, Terry Winograd, has championed the view that human intelligence is less algorithmic and symbolic than what AI researchers have come to believe. The HCI approach has therefore focused on a design approach that emphasizes interpretation, behaviors, and experimentation.

However, HCI is not the only perspective to human-computer symbiosis. Large-scale computational problems often cannot be solved by either computer or humans alone. This issue is known as “human computation problems.” For instance, crowd-sourcing strategies for many messy, large-scale image or character recognition problems fall into this domain. Human computation problems rely on harnessing human processing power (i.e., common sense) to solve problems that computers are not yet good at explaining. More interestingly, many early human computation problem-solving approaches have utilized gamification strategies that align with the HCI tradition of the design approach.

Given the increasing role AI plays in society today, the White House issued a Request for Information (RFI) in 2016 to solicit commentaries and feedback on the role of AI for current and future needs of the economy. A report summarizing the responses to the RFI was released recently by the White House.

IBM’s response to the RFI declared an emphasis on augmented intelligence in IBM’s approach to AI:

“We call our particular approach to augmented intelligence … Cognitive computing is a comprehensive set of capabilities based on technologies such as machine learning, reasoning, and decision technologies; language, speech, and vision technologies; human interface technologies; distributed and high-performance computing; and new computing architectures and devices. When purposefully integrated, these capabilities are designed to solve a wide range of practical problems, boost productivity, and foster new discoveries across many industries.”

Google’s approach to AI, especially its search engine design, is also arguably more in the tradition of IA than AI.

We expect to see some thought-provoking research in this year’s conference. I hope to share some insights from the workshop at the end of the year. In the meanwhile, I welcome your thoughts and ideas on the future role of AI for society.