IBM is one of a large number of companies that are deeply engaged in developing uses of Artificial Intelligence (AI) to help solve problems and accomplish tasks (Moursund, 2017a). In 1997, an IBM computer system named Deep Blue defeated the reigning world chess champion in a six-game match. In 2011, an IBM computer system named Watson handily defeated former Jeopardy! winners Brad Rutter and Ken Jennings.
A recent interview of Ginni Rometty, Chief Executive Officer of IBM, discussed what that company is currently doing (Murphy, 9/25/2017). The interview began with Rometty explaining why IBM now uses the terminology Cognitive Computing rather than AI. Quoting Rometty:
When we started [our major emphasis on AI] over a decade ago, the idea was to help you and I make better decisions amid cognitive overload. That’s what has always led us to cognitive. … It’s the idea that each of us are going to need help on all important decisions. I’m always reminded of an interesting statistic: When you’re asked what percentage of your decisions are right, what percentage would you get [estimate]?
A study said on average that a third of your decisions are really great decisions, a third are not optimal, and a third are just wrong.
The basic underlying question is to what extent can a computer system be a cost-effective aid to help people and companies make better decisions.
If we use a rather broad definition of decision, then I am using computer aids whenever I use my word processor. For example, as I sit keyboarding this IAE Blog entry, I make misspellings and typos. My computer system identifies most of these and makes suggestions on possible corrections. The same system checks my sentence construction (grammar) and makes suggestions for improvements.
Carrying this example a little further, I frequently make use of a Web search engine to do fact checking while I write. This helps me to avoid the error (that is, a type of bad decision) of including incorrect information in what I am writing. A really smart computer system would understand what I am writing and would automatically do fact checking for me. However, we are a very long way from having this level of cognitive computing.
I have written an IAE-pedia article about Information Underload and Overload (Moursund, 2017c). In my daily life, I have access to far too much information that I find interesting and relevant to my life. This is Information Overload. At the same time, I don’t always have easy access to the quite specific information that I need to make a number of the decisions required in a typical day. This is Information Underload. For example, when I am reading a technical article, I often don’t understand it very well. When I make recommendations on how to improve our educational systems, I know only a modest amount about school systems throughout our country—much less about school systems throughout the world.
I also experience information underload when I attempt to explain a personal medical problem to one of my doctors, but don’t have enough medical knowledge to formulate my statement in a manner that accurately communicates my problem. And, what about my doctors? My doctors can know only a small percentage of the accumulated medical research findings. One of IBM’s projects is to provide the Watson computer system with much of the medical research data, including findings from the million or so new medical articles published each year. IBM’s goal is to develop a system that will provide doctors with the information they need to help them to make better decisions.
Here is another quote from the Rometty interview that I found particularly interesting:
When we did our very first oncology teaching with Watson—the very first was lung, breast, and colon cancer—it took the doctors a year to train Watson [about one particular type of cancer].
This is really another key point about professional AI. Doctors don’t want black-and-white answers, nor does any profession. If you’re a professional, my guess is when you interact with AI, you don’t want it to say, “Here is an answer.” What a doctor wants is, “OK, give me the possible answers. Tell my why you believe it. Can I see the research, the evidence, the ‘percent confident’? What more would you like to know?” The first cancer Watson [was trained on] took almost a year. We are down to less than 30 days now. By the end of this year, Watson will have been trained on what causes 80 percent of the world’s cancers (Murphy, 9/25/2017).
The Web is huge, and it continues to grow. Specialized Cognitive Computing systems are being developed by a number of different companies in a number of different areas. When I make use of the Google search engine (which I frequently do), the computer system is keeping track of what I am searching for, how many of the websites it identifies that I actually open, and so on. This information is used both to improve the information retrieval system and to allow Google to target ads that it “thinks” might influence my buying decisions. While the Google search engine is free, I am actually paying for using it by the ads it is presenting to me.
What You Can Do
We have all grown up in a world in which people and machines work together to solve problems and accomplish tasks. Historically most of these tools helped to extend our physical capabilities.
What has changed is that we now have machines that provide us with cognitive help to extend our mental capabilities. Our schools need to help students learn about the capabilities and limitations of Cognitive Computing. I strongly believe that this type of instruction, and the use of such capabilities, should be thoroughly integrated into PreK-12 schooling and higher education.
For more on this topic see my free book, The Fourth R (Moursund, 2016). In addition to Reading, wRiting, and aRithmetic, today’s students need to be learning about Reasoning (Computational Thinking). Computational Thinking makes use of both human brains and computer brains to solve problems and accomplish tasks (Moursund, 2017b). Computational Thinking is a critical human component of Cognitive Computing.
References and Resources
Moursund, D. (2017a). Artificial Intelligence. IAE-pedia. Retrieved 10/16/2017from http://iae-pedia.org/Artificial_Intelligence.
Moursund, D. (2017b). Computational thinking. IAE-pedia. Retrieved 10/16/2017 from http://iae-pedia.org/Computational_Thinking.
Moursund, D. (2017c). Information underload and overload. IAE-pedia. Retrieved 10/15/2017 from http://iae-pedia.org/Information_Underload_and_Overload.
Moursund, D. (12/23/2016). The Fourth R. Eugene, OR: Information Age Education. Download the Microsoft Word file from http://i-a-e.org/downloads/free-ebooks-by-dave-moursund/289-the-fourth-r/file.html. Download the PDF file from http://i-a-e.org/downloads/free-ebooks-by-dave-moursund/290-the-fourth-r-1/file.html. Access the book online at http://iae-pedia.org/The_Fourth_R.
Murphy, M. (9/25/2017). Ginni Rometty on the end of programming. Bloomberg Businessweek. Retrieved 10/15/2017 from https://www.bloomberg.com/news/features/2017-09-20/ginni-rometty-on-artificial-intelligence.
Free Educational Resources from IAE
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- IAE-pedia. See http://iae-pedia.org/index.php?title=Special:PopularPages&limit=250&offset=0.
- IAE Newsletter. See http://i-a-e.org/iae-newsletter.html.
- IAE Blog. See http://i-a-e.org/iae-blog.html.
- IAE books. See http://iae-pedia.org/David_Moursund_Books and http://iae-pedia.org/Robert_Albrecht#Free_Books_by_Bob_Albrecht.