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We made it through 2016, and now it’s that time when we reflect on a year gone by.<\/p>\n
Best of 2016<\/strong><\/p>\n There were several cool breakthroughs in math this year. My personal favorite involved the famous question of how to optimally stack higher dimensional spheres in space<\/a>. This year Maryna Viazovska made a critical breakthrough<\/a>, solving the 8-dimensional case, and several weeks later the 24-dimensional case tumbled too. This breakthrough is an important one because of its applications to coding theory and data transmission. When the result was announced Quanta published a very thorough history<\/a> of the sphere packing problem that led to the breakthrough.<\/p>\n This year we also found some interesting (and huge!) new primes. The world record for longest known prime is now 22,338,618 digits.<\/a> This bad-boy is a Mersenne Prime<\/a>. In September there was also a new world record set for the largest twin primes<\/a>. If we printed out all the new prime goodness we found this year it would take about 20 reams of printer paper.<\/p>\n My favorite math in pop culture this year was The Man Who Knew Infinity<\/a><\/em>, the film about Ramanujan and Hardy. If you haven’t seen it yet, I urge you to. Several great books about math also came out this year, including Cathy O’Neil’s Weapons of Math Destruction<\/a><\/em> about the dangers of data science, and Margot Lee Shetterly’s Hidden Figures<\/a><\/em> about a group of African American woman mathematicians who contributed to the space race. I just received the latter as a gift for christmas, so you can expect a review of that in the next few weeks.<\/p>\n Worst of 2016<\/strong><\/p>\n The real computational dunce cap of the year definitely goes to Facebook and their biased newsfeed algorithms<\/a> that proliferated fake news during an historic and incredibly tense election. Cathy O’Neil did a nice job covering news<\/a> of all things algorithmic this year before, during, and after the election. In general, this also reminds of the trouble we’ve had with bias in algorithms this year. For example, that algorithm that was supposed to help the legal system by predicting criminal behavior and instead has just contributed to our already incredibly racist justice system<\/a>. I guess this was the year to remember that algorithms are run by computers, but written by humans.<\/p>\n On the theme of politics, it was a weird and bad year for polling too. I suppose we learned the value of 2 percentage points<\/a>, and learning is a good thing, but I suspect we also had a false sense of reality going into the elections and that was a bad thing. While the speed with which we can consume infographics and data makes is quicker to digest numbers, it also leaves us with a pretty poor understanding of what’s going on in the margins<\/a>. The lesson we learned here is that numbers need context.<\/p>\n And finally, the absolute worst of the worst this year (and perhaps a partial solution to the problem of the previous paragraph) was this craziness about the myth of algebra that just won’t seem to quit. I’m talking, of course, about Andrew Hacker and his infamous call to arms against mandatory high school algebra<\/a>. This year he wrote a book on the subject, and I will concede that he makes a few good points about numeracy and problem solving<\/a>. But he also makes dozens of horrible points about some made up algebra straw man that forces you to compute azimuths<\/a>. So, I’m sorry Hacker, I just can’t. We need Algebra. So much Algebra.<\/p>\n Have a happy new year! And to all of you who are traveling to the JMM in Atlanta, have safe and speedy travels and stay tuned for our 2017 Joint Meetings Blog<\/a>.<\/p>\n