Threat is all about context
Threat is all about context. Actually, one of many greatest dangers is failing to acknowledge or perceive your context: That’s why you might want to start there when evaluating danger.
That is significantly necessary by way of fame. Assume, as an example, about your prospects and their expectations. How would possibly they really feel about interacting with an AI chatbot? How damaging would possibly it’s to supply them with false or deceptive info? Possibly minor buyer inconvenience is one thing you possibly can deal with, however what if it has a major well being or monetary affect?
Even when implementing AI appears to make sense, there are clearly some downstream fame dangers that should be thought of. We’ve spent years speaking concerning the significance of consumer expertise and being customer-focused: Whereas AI would possibly assist us right here, it may additionally undermine these issues as nicely.
There’s an identical query to be requested about your groups. AI might have the capability to drive effectivity and make folks’s work simpler, however used within the mistaken approach it may severely disrupt current methods of working. The trade is speaking rather a lot about developer expertise lately—it’s one thing I wrote about for this publication—and the choices organizations make about AI want to enhance the experiences of groups, not undermine them.
Within the newest version of the Thoughtworks Expertise Radar—a biannual snapshot of the software program trade primarily based on our experiences working with shoppers all over the world—we discuss exactly this level. We name out AI staff assistants as one of the thrilling rising areas in software program engineering, however we additionally notice that the main target must be on enabling groups, not people. “You ought to be in search of methods to create AI staff assistants to assist create the ‘10x staff,’ versus a bunch of siloed AI-assisted 10x engineers,” we are saying within the newest report.
Failing to heed the working context of your groups may trigger important reputational harm. Some bullish organizations would possibly see this as half and parcel of innovation—it’s not. It’s displaying potential staff—significantly extremely technical ones—that you just don’t actually perceive or care concerning the work they do.
Tackling danger via smarter know-how implementation
There are many instruments that can be utilized to assist handle danger. Thoughtworks helped put collectively the Accountable Expertise Playbook, a group of instruments and strategies that organizations can use to make extra accountable choices about know-how (not simply AI).
Nonetheless, it’s necessary to notice that managing dangers—significantly these round fame—requires actual consideration to the specifics of know-how implementation. This was significantly clear in work we did with an assortment of Indian civil society organizations, growing a social welfare chatbot that residents can work together with of their native languages. The dangers right here weren’t not like these mentioned earlier: The context during which the chatbot was getting used (as help for accessing important providers) meant that incorrect or “hallucinated” info may cease folks from getting the sources they depend upon.
