A.I projects require massive amounts of data to be of any use. 80% of the work done when creating an algorithm involves data extraction, cleansing, filling, and normalizing to make sure simple errors can be systematically avoided. Algorithms have the ability to systematically “make” unfair decisions without anyone noticing, or even understanding why, making ethics more relevant than ever. As such, teams should make sure that the data is representative reality, and that it does not reflect reality’s existing prejudices.


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@adrien-bookAdrien Book

Strategy Consultant | Tech writer at http://ThePourquoiPas.com | AI writer of the Year | http://my.bio/adrienbook

By now, all self-respecting executives have heard of A.I and thought “Mmhm, yeah, I’d like to get myself a piece of that action”. And because they’re executives, they told underlings to get it going, and went back to the golf course. I personally see no problem with that way of doing things, as the underlings then go to consultants such as myself to understand what their boss could have possibly meant by “I want, like, Alexa, but, like, for office chairs” (yes, I have a PowerPoint presentation for that).

There are however a few risks I believe should be considered BEFORE replacing all the chair-whisperers by an algorithm. Indeed, mentally asking oneself the questions below before jumping into an A.I project might mitigate risks, save time, money, and make both the BUILD and RUN part of said project a lot smoother.

It does not replace in any way, shape or form the due diligence necessary to get such an endeavor off the ground, but provides a useful framework to start a constructive conversation.

1. Do I have a SMART goal ?

Regardless of their coding or data analysis abilities, the people at the top have a key role to play in defining the strategy for an A.I project. Does the company want to disrupt its market by creating a different type of value proposition à la Amazon? Does it seek to be best in class, à la Amazon ? Maybe it aims to stay level on a competitive market, à la Amazon ? Or even catch up to a leader, à la Amazon ?

You know, I’m starting to sense a trend.

Without being given such a direction, teams will be left to aimlessly dig through data, looking for a story. And with no clear and agreed-upon goal, they’ll be left chasing a moving target, running the risk of rewriting history as the data comes in. That’s why the strategy defined BEFORE any project kick-off…

Continue reading: https://hackernoon.com/10-questions-to-consider-when-setting-up-a-corporate-a-i-project-f7cc2a50188d?source=rss

Source: hackernoon.com