IEEE P7011 Working Group

Engineering, Imprecision, the 2nd Law of Thermodynamics, and Fake News

By Donald Bryson

The invention that swells me with the most pride would have been a massive failure. In 1971, as a 14-year-old boy, I took a job sweeping the parking lot of the little grocery store in my hometown. I had an idea that I could build a robot to sweep the parking lot. I talked to the owner of the store, who might have laughed behind my back but never to me face, into a generous quantity of pads and colored pencils for the design phase. I drew my diagrams, did my math, and made my presentation. Fortunately, Mr. Henley decided that paying 14-year-old boys was cheaper than breaking into the robotics business in 1971. My design would have ‘theoretically’ worked. However, I hadn’t discovered that things are never black and white, and the universe moves toward entropy. My measurements might have been good enough to keep the robot out of the road for a short time, but I doubt it. However, I am sure that rotors, gears, and tires change over time and abstract math does not.  My robot would have certainly wandered into a busy road eventually much to the surprise of some poor Georgian motorist.

I told that lengthy story to remind us of two realities – measurements are never perfectly precise, and the universe moves toward entropy. Yet, engineers  naturally hate imprecision and guesses. Software, devices, and controls fail because of faulty measurements. We all have stories of something being 4.5 instead of 4.4 and triggering an embarrassing professional moment. Engineers hate entropy. We all have stories of a random event triggering a software failure after we tested code ten times in an orderly fashion.

We need to always make the distinction in our own mind of the difference between degree of precision and false. The classic example of that distinction is the inferred calculation of pi in the Bible. I Kings 7:23 seems to say that pi is 3.0 because it gives a circular bowl as having a circumference of 30 and a diameter of 10. However, those measurements are in cubits which is the length from the elbow to the extended fingertips which is certainly not the most precise unit of measurement.  We deal with information in the public discourse that is equally as imprecise. Consider the unemployment rate. Although U-3 is the one most often cited in the media, there are other ways the Department of Labor calculates the unemployment rate and you are never completely sure which one is being cited. It is imprecision but not fake news when one reporter writes the U-3 rate and it does not match the U-5 reported by another.

We also must approach this subject with an appreciation of the entropy in the universe. For example, a reporter may go to a political event that is generally well received. However, they randomly wander into a section of the crowd with a large family that hate this cause or candidate. The reporter reports the event as he/she sees it.   It is not fake news when a reporter writes about the random outlier. True, they should have checked more but reporting what they saw and heard is not fake news. It is an example of entropy in the universe. Moreover, some degree of inconsistency speaks to the validity of different accounts of the same event. Let’s say you are a chaperon for your child’s school event. A lamp is broken with only the children in the room. You walk into the room and the same exact story is repeated by every child. That makes their story hard to believe.

Let’s think of a thought experiment from our profession. You have a device or process that requires quality assurance tests results from some measuring device. Three testers return with the same exact Gaussian data points. Again, that is hard to accept as valid information. Prominent data scientist, Jeff Jonas, states that, “Some bad data is good” when he is contrasting his G2 paradigm with master data management (MDM) because bad data helps define and quantify what is known (see Sensemaking and its 7 Secret Sauces ).

Please do not misunderstand what I am saying. I hate fake news and I believe fake news is created by evil people with evil intentions. Propaganda paralyzes democracy. Moreover, it degrades the value of the legitimate media as their perceived trustworthiness falls. The work this group will be doing is critical.

Our professional training and experience gives us a unique set of tools to help a society with truth and free speech under attack. But, some of the attributes that make a great engineer or computer scientist need to be tempered. We love precision and order. However, the world is imprecise and evolving chaos. Multiple news articles about one event should have different vantage points. A crowd could look like it is massive from one vantage point while not that large from another one. The economy looks bad if you are interviewing the unemployed yet great if you are interviewing the CEO of the next hot company.  Our standard must be geared to fit the world as-it-is rather than our natural predisposition.

“The massive new study analyzes every major contested news story in English across the span of Twitter’s existence—some 126,000 stories, tweeted by 3 million users, over more than 10 years—and finds that the truth simply cannot compete with hoax and rumor. By every common metric, falsehood consistently dominates the truth on Twitter, the study finds: Fake news and false rumors reach more people, penetrate deeper into the social network, and spread much faster than accurate stories.”

The MIT study published in Science the above article references can be found here:

The New York Times podcast The Daily discusses some of the risks and threats created by foreign actors interfering with news and information channels.  Note the usage of terms like, “trustworthy” in the context of news stories on Facebook.

Episode Description:

The indictment secured by the special counsel, Robert S. Mueller III, makes it clear that the most powerful weapon in Russia’s campaign to disrupt the 2016 election was Facebook. We look at how Russia used social media to sow divisions in the United States.

Guest: Kevin Roose, who writes about technology for The New York Times.

For more information on today’s episode, visit