Have you ever gotten a recommendation from Netflix or Amazon
or Spotify for a book or movie or song that you didn’t think you would like,
but took a chance and really liked it?
Did you think, “Wow, Netflix knows me better than I know myself!” Or at
least their data science/collaborative filtering/content filtering algorithm
does.
This really shouldn’t be surprising. Algorithms like Amazon’s product
recommendation and Pandora’s music genome project can consider thousands of
variables, millions of users’ behaviors, and millions of products to find just
the right ones for you at that time and place.
If the algorithm is designed well and implemented with the right UX of
course. There are many disasters as
well. But we create disasters of our own
too – I can think of a few movies I really wanted to see that turned out to be
horrible.
Now jump ten years into the future when the targeting gets
an order of magnitude better. It adds
emotion monitoring (which has actually just been launched as an app by
Affectiva), activity monitoring (through your fitness tracker), and whatever
else gets invented in the near future.
This would still not be perfect, but might be reliably
better than we are ourselves. Enough that we trust it to be as good as we would
be, and more convenient because we don’t have to bother with the search, sort,
and choose process.
Now add another step.
Skip the middle man and let those companies actually make the decision
for us. If we read a book a week, Amazon can simple decide what we are most
likely to enjoy and ship it. We log on to Netflix and the queue is full of TV
shows and movies that it knows we will enjoy.
If that works so well, why not broaden our thinking? The food vendor knows just what we feel like eating
for dinner based on our past eating history, taste preferences, activities that
day, current stress levels, and nutritional needs. So as we are getting home
from work the drone is dropping off the ingredients we need (or for those who
don’t like to cook, the takeout drone delivers dinner ready made). On stressful days we get our favorite comfort
food. On workout days we get a balanced protein/veggie/carb combo. You get the idea.
Michael Sandel at Harvard gave me an even better
application. The frequency of bad dates and the high divorce rate prove that we
are not particularly good at finding romantic partners. Maybe Match or eHarmony’s
algorithms will get good enough that we can absolve ourselves of that
responsibility as well. Instead of
suggesting dates, they will jump right to arranging marriages.
That has kind of a “full circle” vibe to it, doesn’t it?
