AI and IA

Before AI, the "lazy" intelligence analysts just copied and pasted from whatever combination of OSINT they could find on their topic. In contrast, the "serious" analysts mulled over veracity, nuances, purpose, client preference, framing, SAT's and visualization. 

Depending on urgency, client appetite, and expectations, the "in-betweeners" are chameleoned between the two modes. If your clients did not care about how you got to your key judgments, you produced for production and visibility's sake. 

Those analysts, peers, managers and clients who cared about impact and doing the right thing forced us to be professional, dig deeper and think wider.

These fundamentals are still the same: the lazy analysts, managers and clients have just multiplied.

What has changed in the AI age is that we don't need to search for OSINT; bespoke aggregators and AI force-feed us. 

Also, clients, sometimes managers, have a much shorter attention span and less appetite for the truth and professional conduct. They don't care what we think or what analytical techniques led us there. They have their own existential and political battles to fight. We work for clients who have changed their perception of the value of intelligence, while we hope and pray that we can still impact their decision-making.

It's as if the "war against science and truth" has become our bed partner in a forced marriage. "Quick and sexy" intelligence deliverables and shallow thinking lead to the demise of analytical rigour. 

There is no easy answer to the problem of lazy analysts and managers, know-it-all clients, or "AI idiots," courtesy of Dion Wiggins. Read his article https://lnkd.in/eu_XvUGB

But one thing is certain: we should strengthen the AI competencies of the "serious" analysts and try to "professionalize" the chameleons.

We do this by learning, teaching, and showing how AI can effectively help us with the grunt work while providing a thinking partner to enhance our analytical praxis. 

Nico Dekens (Dutch_OsintGuy)'s article, as well as Wiggin's practical advice in https://lnkd.in/ewS4xXmM is a good start!