Nov 9, 2018
<p>Even though we live in an era of "big data" and huge
amounts of our internet usage and content consumption are governed
by algorithms (Facebook's newsfeed, YouTube's related videos,
Google's predictive search, the advertising we're served online,
etc.), many people don't trust algorithms when they're presented
with the opportunity to use them in their own
decision-making.</p>
<p>Berkeley Dietvorst thinks this results in people
making a lot of very foolish decisions, and wasting a lot of time,
money, and effort.
So, he's been researching the concept of "algorithm aversion" for
several years and he's published several highly illuminating papers
on the topic.</p>
<p>Berkeley has developed a theory of why humans don't like
to use algorithms (they're probably chasing perfection in their
predictions and they excessively punish algorithms for making
visible errors) and he continues to work on understanding ways in
which we can increase the trust that human decision-makers place in
algorithms.</p>
<p><b>Check out more from Berkeley
here:</b><li>Website: <a
href="http://faculty.chicagobooth.edu/berkeley.dietvorst/index.html">Berkeley's
Chicago Booth Profile</a>//<a
href="http://faculty.chicagobooth.edu/berkeley.dietvorst/research/index.html">Berkeley's
Research</a></li></p>
<p><b>If you're enjoying the show, <a
href="https://itunes.apple.com/us/podcast/todd-niefs-show/id1278759120?mt=2">why
not a leave a review</a>?</b> It makes a difference in
terms of other people finding the show.</p>
<p><b>You can also subscribe to receive my e-mail
newsletter at <a href="http://www.toddnief.com">www.toddnief.com</a>.</b>
Most of my writing never makes it to the blog, so get on that
list.</p>
<p><b>Show Notes</b><ul> <li>[1:28]
Berkeley is a marketing professor - yet studies algorithm
aversion</li>
<li>[4:22] Humans are algorithmically averse - what’s our
problem?</li>
<li>[12:10] Humans are risk-seeking so will choose not to use
algorithms in order to seek outsized reward</li>
<li>[19:02] Humans err by regularly changing the weighting
they give things based upon emotions</li>
<li>[26:22] Humans are more likely to use algorithms when
they’re allowed to modify an algorithm</li>
<li>[35:20] Increasing human adherence to using superior
algorithms to make predictions</li>
<li>[40:58] Are there ever good reasons for humans to
distrust algorithms?</li>
<li>[1:04:17] How do we optimize the decision-making for
individual decision-makers? And what would Berkeley like to know
about how large tech companies get humans to use
algorithms?</li>
<li>[1:11:15] How can people learn more about Berkeley’s
research? And what research projects is he currently working
on?</li>
</ul></p>
<p><b>Links and Resources Mentioned</b><ul>
<li><a href="https://www.chicagobooth.edu/">The
University of Chicago Booth School of
Business</a><br/></li>
<li><a href="https://www.wharton.upenn.edu/">The
Wharton School</a><br/></li>
<li><a
href="https://www.predictiveanalyticsworld.com/patimes/target-really-predict-teens-pregnancy-inside-story/3566/">Did
Target Really Predict a Teen’s
Pregnancy?</a><br/></li>
<li><a
href="https://www.nytimes.com/2011/08/21/magazine/do-you-suffer-from-decision-fatigue.html">Do
You Suffer From Decision
Fatigue?</a><br/></li>
<li><a
href="https://en.wikipedia.org/wiki/Robyn_Dawes">Robyn
Dawes</a><br/></li>
<li><a
href="https://en.wikipedia.org/wiki/CompStat">CompStat</a><br/></li>
<li><a
href="https://medium.com/">Medium.com</a><br/></li>
<li><a
href="https://fivethirtyeight.com/contributors/nate-silver/">Nate
Silver –
FiveThirtyEight</a><br/></li>
<li><a href="https://magic.wizards.com/en">Magic: The
Gathering</a><br/></li>
<li><a href="http://dnd.wizards.com/">Dungeons
& Dragons</a><br/></li>
</ul></p>