Danger is all about context
Danger is all about context. In truth, one of many largest dangers is failing to acknowledge or perceive your context: That’s why you should start there when evaluating threat.
That is notably essential by way of repute. Suppose, as an illustration, about your clients and their expectations. How would possibly they really feel about interacting with an AI chatbot? How damaging would possibly it’s to offer them with false or deceptive info? Possibly minor buyer inconvenience is one thing you may deal with, however what if it has a major well being or monetary impression?
Even when implementing AI appears to make sense, there are clearly some downstream repute dangers that have to be thought-about. We’ve spent years speaking in regards to the significance of consumer expertise and being customer-focused: Whereas AI would possibly assist us right here, it may additionally undermine these issues as effectively.
There’s the same query to be requested about your groups. AI could have the capability to drive effectivity and make folks’s work simpler, however used within the incorrect method it may significantly disrupt current methods of working. The trade is speaking lots about developer expertise not too long ago—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 Know-how Radar—a biannual snapshot of the software program trade based mostly on our experiences working with purchasers all over the world—we speak about exactly this level. We name out AI group assistants as probably the most thrilling rising areas in software program engineering, however we additionally word that the main focus must be on enabling groups, not people. “You ought to be on the lookout for methods to create AI group assistants to assist create the ‘10x group,’ 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 vital reputational harm. Some bullish organizations would possibly see this as half and parcel of innovation—it’s not. It’s displaying potential staff—notably extremely technical ones—that you simply don’t actually perceive or care in regards to the work they do.
Tackling threat by smarter know-how implementation
There are many instruments that can be utilized to assist handle threat. Thoughtworks helped put collectively the Accountable Know-how Playbook, a set of instruments and strategies that organizations can use to make extra accountable choices about know-how (not simply AI).
Nevertheless, it’s essential to notice that managing dangers—notably these round repute—requires actual consideration to the specifics of know-how implementation. This was notably 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 in contrast to these mentioned earlier: The context wherein the chatbot was getting used (as assist for accessing very important providers) meant that incorrect or “hallucinated” info may cease folks from getting the sources they rely upon.
