Tackling AI risks: Your reputation is at stake

Threat is all about context

Threat is all about context. The truth is, one of many largest dangers is failing to acknowledge or perceive your context: That’s why you could start there when evaluating threat.

That is notably vital when it comes to fame. 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 supply them with false or deceptive data? Perhaps minor buyer inconvenience is one thing you possibly can deal with, however what if it has a major well being or monetary influence?

Even when implementing AI appears to make sense, there are clearly some downstream fame dangers that should be thought-about. We’ve spent years speaking concerning the significance of consumer expertise and being customer-focused: Whereas AI would possibly assist us right here, it might additionally undermine these issues as properly.

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 incorrect approach it might significantly disrupt present methods of working. The business is speaking quite a bit 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 Know-how Radar—a biannual snapshot of the software program business based mostly on our experiences working with shoppers around the globe—we discuss exactly this level. We name out AI workforce assistants as one of the crucial thrilling rising areas in software program engineering, however we additionally notice that the main focus needs to be on enabling groups, not people. “You need to be on the lookout for methods to create AI workforce assistants to assist create the ‘10x workforce,’ 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 might 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—notably extremely technical ones—that you just don’t actually perceive or care concerning the work they do.

Tackling threat by way of smarter expertise implementation

There are many instruments that can be utilized to assist handle threat. Thoughtworks helped put collectively the Accountable Know-how Playbook, a group of instruments and methods that organizations can use to make extra accountable selections about expertise (not simply AI).

Nevertheless, it’s vital to notice that managing dangers—notably these round fame—requires actual consideration to the specifics of expertise implementation. This was notably clear in work we did with an assortment of Indian civil society organizations, creating 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 by which the chatbot was getting used (as help for accessing very important companies) meant that wrong or “hallucinated” data might cease folks from getting the sources they depend upon.