Seeing past the hype around cognitive computing – Jeanne Ross

Jeanne Ross, Director & Principal Research Scientist at the MIT Sloan School's CISR

Jeanne Ross, Director & Principal Research Scientist at the MIT Sloan School’s CISR

From Information Management

Given the hype around artificial intelligence, you might be worried that you’re missing the boat if you haven’t yet invested in cognitive computing applications in your business. Don’t panic! Consumer products, vehicles, and equipment with embedded intelligence are generating lots of excitement. However, business applications of AI are still in the early stages.

Research at MIT Sloan’s Center for Information Systems Research (CISR) suggests that small experiments in cognitive computing may help you tap the significant opportunities AI offers. But it’s easy to invest huge amounts of cash and time in failed experiments so you will want to carefully target your investments.

The biggest impact from cognitive computing applications is expected to come from automation of many existing jobs. We expect computers to do—faster and cheaper—many tasks now performed by humans. Progress thus far, however, suggests that we have significant obstacles to overcome in our efforts to replace human intelligence with computer intelligence. Despite some notable exceptions, we expect the displacement of human labor to proceed incrementally.

The business challenge is to determine which applications your company is ready to cash in on while resisting the lure of tackling processes that you can’t cost-effectively teach machines to do well. We have studied the opportunities and risks of business applications of cognitive computing and identified several lessons. These lessons offer suggestions for positioning your firm to capitalize on the potential benefits of cognitive computing and avoid the pitfalls.

Necessary ingredients

Business processes need to meet four conditions to effectively apply cognitive computing. These include:

1) prescribed outcomes

2) lots of repetition

3) massive amounts of relevant, interpretable electronic data

4) complex interactions among the parameters that influence optimal outcomes

AI has been successfully applied to games like chess, Jeopardy, and Go because these games completely meet these conditions.

An example of an effective business use of cognitive computing is Kabbage, which uses AI to determine who should or should not receive a loan, given a company’s predetermined goals (like maximizing interest revenue or minimizing bad loans).

Kabbage has access to vast amounts of personal data because it gets permission from loan applicants to collect their financial information from their financial services providers. Kabbage also scours social media. The loan granting process is highly repetitive and Kabbage can learn from every loan repaid (or not). As the database grows from thousands to millions, the application can repeatedly review its algorithm and assess the impact of new kinds and instances of data.

Read the full post at Information Management.

Jeanne W. Ross is the Director and Principal Research Scientist Center for Information Systems Research at MIT Sloan.

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