Hunch: Inspired Decisions With Collective Knowledge
Hunch, a new decision engine was just launched. It is based on collective knowledge principle, which ensure an increased efficiency of decisions. The user must ask to a set of questions and at the end, Hunch engine will provide a concrete answer, as well as other alternatives, if the answer is not compliant with the user’s expectations. Being powered by a mathematical framework, the decision making algorithm is programmed to determine Hunch to learn from the users answers in order to refine the delivery of decisions.
On the Hunch website FAQ page there is explained the decision engine processing mechanism of user collective knowledge: “When Hunch proposes a decision result, it will also show you why it proposed what it did. If you disagree with some of the reasoning, you can correct it. If you think Hunch missed asking a crucial question, you can submit one. And if you think Hunch is missing a good result, you can add that, too. Hunch collects and organizes all this input so that it becomes smarter for the next user.”
As a consequence, the decision making process is different from a user to another, as a function of the question selection algorithm of Hunch engine. Practically, the provided decision will depend both by an individual user answers, as well as the Hunch engine level of learning in case of a certain topic.
The questions involved in a Hunch topic can be posted on your website with the help of a widget (the HTML code is provided for free). Hunch also allows you to access its data and the embeddable content through an API.
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