Will We Need Analysts in the Age of Artificial Intelligence?

by admin
September 23, 2020
Robot Virtual Computing

Last year I attended the Association of International Risk Intelligence Professional’s (AIRIP) Fall Conference on the future of public- and private-sector intelligence, where the future” part dealt primarily with the tools available to analysts today and with the promise of more powerful, AI-enable tools coming soon. This focus echoed what I heard at last year’s Intelligence and National Security Alliance (INSA) conference, where the application of AI to national security intelligence challenges dominated the presentations I attended. Does this abundant exuberance for AI mean that the days of having humans in the loop of the intelligence cycle are limited?  Obviously, many roles in collection and processing will become increasingly automated, but as a member of Team Human I’m happy to say we’re safe from being completely replaced for now.

Discussion at the AIRIP and INSA events covered how tools can aid the collection, organization, and analysis of information. As Jackie Babieri, CEO and co-founder of Whitespace Solutions, put it in her keynote at the AIRIP conference, these tools help analysts mine and connect the dots. What I haven’t heard people talk much about, however, is how these tools help analysts communicate their findings to customers.  This echoes my experience working at a big data analytics software company, where our tool promised to do amazing things related to finding, connecting, and displaying dots, but it certainly did not write thoughtful analysis or brief its findings to customers.

It’s in this final mile of the intelligence cycle, where analysis is packaged and delivered to customers, that the need for the human touch appears most resilient.  Sure, AI can take the box score of a high school baseball game and write an acceptable summary, but that’s a far cry from providing the context, insight, and forecasting expected by most consumers of analysis. There will always be customers who prefer the raw data, but most are too busy to wade into details and instead want someone to provide the synthesis and insight to meet their specific needs.  This critical role places a premium on analysts with the very human skill of creativity and experience in producing concise, customer-focused analysis.

The good news, of course, is that we won’t have to choose between AI and people in our analytic future; well-trained analysts stand to reap dramatic improvements in efficiency and effectiveness in servicing this final mile when paired with increasingly powerful tools.  Realizing this promise requires tools to be designed with those analysts in mind–an obvious requirement that sadly is not always met.  Success also requires analysts with the right substantive expertise and organizational acumen who are trained not only in how to use these tools but also in the core elements of their craft:  critical thinking, analytic writing, and oral presentation.   Since we are launching Proficiency1, an online training community for analysts, I’m relieved that they are going to be around for a while and that their ability to keep their skills current will be as important as ever.  I’d love to hear what others think about my optimistic assessment of how analysts will fare in an AI-dominated future.