How automating feedback with AI powered conversations can aid decision making in real-time
All systems need feedback to learn, improve and course correct. The autopilot functionality in driverless cars is a perfect example. Sensors measure the desired speed and position of the vehicle — among other indicators — and send that data to control systems which adjust accordingly.
Gathering rich, organic feedback on a continuous basis is necessary for managers and regulators to make informed decisions. Robust feedback means honoring people’s authentic voices, rather than shoehorning them into a multiple choice format. It means taking the time to find out how many others share what may be a surprising opinion (to management) or understanding of a situation. It means preserving minority opinions. It means listening well.
But getting rich feedback from a population usually starts with in-depth interviews of a representative sample. Surveys are then created based on the interviews to see which ideas are representative. The process is manual, time consuming and requires specialized knowledge — in a word, expensive.
Applying artificial intelligence to the problem of gathering insights from large populations alleviates much of the burden. AI assisted feedback gathering means no routine effort or process on the part of the organization. It realizes, in yet another domain, Licklider’s vision of human computer symbiosis:
Licklider[’s] … vision was to enable man and machine to cooperate in making decisions, controlling complex situations without the inflexible dependence on predetermined programs. … Licklider foresaw computers doing all the routinizable work that was required to prepare the way for insights and decision making. — Shyam Sankar, TEDGlobal 2012
It means genuine, rich feedback can appear in the inboxes of those who need it, from those who are best positioned to give it, every day or every week — as often as makes sense. It also means that feedback can be scripted or scheduled to run in a certain way at a certain time, in extremely flexible ways.
Most importantly, though, it means organizations have the potential to learn and improve on ideas more quickly.
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