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How I Learned to Stop Worrying, Part 2: Algorithms Make Us More Human

Sep 2011/in /by

Recently, my colleague Ryan Warren made some astute comments about the emerging importance that algorithms are now playing in our economy, society and daily lives. Like Ryan, I believe that smart people writing creative algorithms are the guts and magic that glue together much of the wonder and advancement in modern life. Algorithms are tools, and in the end, it’s the use of tools that make us fundamentally human.

I am often surprised how when reading articles, technical papers and reading the news, how a particular phrase pops out and hits me. The human mind is an amazing thing: It’s ability to take in, digest and synthesize information is magic. It’s like an “ah-ha” moment when out of all the text, information and perspective, a particular phrase catches the eye, stimulates the old grey matter and in a split-instant a new connection is made.
As I read Jane Wakefield’s recent article on BBC News, I had one such moment. As I was reading, the following quote caught my eye:

“Increasingly … we are knowing where information can be found rather than retaining knowledge itself.”

Suddenly, I found myself thinking about watching Donald Trump in an episode of the Apprentice, and then being involved in yearly business strategy meetings at several companies I have had the pleasure to work at, and then on to the several years consulting with Companies related to branding and marketing challenges.

And thus, new connections were made. In each of these situations, people were being asked to work on projects where they had to rapidly become experts in a subject area, enough to make and execute on business plans. And today, this is far from uncommon. With the pace and demands on today’s knowledge workers—business professionals who need information on which to base their daily decisions—and the inexorable drive towards higher efficiency and productivity, major changes in how we work are occurring. For example:

• Knowledge workers now move from project to project, with few jobs remain static in their responsibilities. A Marketing Professional may be writing an op-ed article one day, and the next working on the company’s strategic plan.
• Self-service is now the way of working. Why ask a researcher or admin to get information, when there are tools out there like the Web where information can be at hand in a matter of minutes or even seconds?
• Just-in-time information delivery is now expected, with no tolerance for waiting days for information to be delivered, and thus …
• The speed of work is increasing. The ability to rapidly understand a project’s business requirements, be able to do essential subject matter research, and get up to speed fast is essential, as successful professionals are those who are viewed as having a track record of working on fast, high-impact projects.

And a thread common to all these developments is that success is now often determined by a person or team’s ability to rapidly acquire information and data upon which to base implementation and operational decisions.

In this kind of environment, the need for a tool like FirstRain was perhaps inevitable. With FirstRain Monitors, business professionals can easily track the markets, companies and business-related topics that are of interest to them. They are easy to setup and provide current, daily or weekly updates. In today’s business world, business monitoring needs to be useful quickly and have value only for the duration of the project being worked on now. FirstRain’s display engine responds to this by preferentially displaying a user’s most recently active Monitors.

But our new just-in-time paradigm has risks. Our understanding of the meaning of content requires context and interpretation, and this can take time we’re often unwilling to wait for. Viewed in isolation, a piece of news may seem to have a very different meaning than it does when combined with the right historical context.

YHOO: Previous 7 Days

YHOO: Previous 1 Year

For example, an examination of Yahoo!’s results over the last week tells a very different picture than would see once you step back and look at that firm’s performance over the last year. The human mind is a great tool for synthesizing perspective based on long-term acquired knowledge—we call this learning. And it is the connection between news items and other pieces of information that provides context and the tools for critical discernment—as professionals we call this experience. Our individual ability to make smart decisions is based on the information at hand, processed through all the biases and filters represented by our past experiences and personal beliefs. To succeed and make smart decisions, we need a mixture of the right data, the right tools, the right context and the right experience. Algorithms, and tools like FirstRain, can help by providing not just the news, but timelines of related significant events and topics of further interest.

In the end, it’s the man-machine combination that creates a unique ability to assimilate information, synthesize pertinent results and make sound business decisions. In other words, it’s a continuation of that amazing innovation that’s helped us succeed as a species: the ability to make and use tools—tools that feed us, that shelter us, that move us, and that deliver us the information we need to shape our world.

human

How I Learned to Stop Worrying, Part 1: Algorithms Make Us More Human

Aug 2011/in /by

An interesting commentary this week by BBC News’ Jane Wakefield commenting on the increasing influence of algorithms in our daily life has gotten a fair amount of play. And indeed, it’s a useful and thought-provoking piece, if for no other reason that we probably can’t emphasize enough the emerging importance that algorithms are now playing in our economy, society and daily lives.

But where Wakefield’s article falls short is in its vaguely menacing tone, patching together random examples of algorithms at use and the trial and error process of putting them to work effectively—all while implying that the extensive use of these algorithms will lead us to some unfortunate yet unspecified problem (my favorite part was her concern over an algorithm being used to determine a potential movie’s marketability in advance of making the movie—because Hollywood movie producers never made such cynical greenlight decisions before they were corrupted by algorithms …). And even more unfortunate, she completely fails to acknowledge the truly amazing things we can now accomplish because of our ability to employ algorithms.

For every example of an algorithm that has wreaked havoc due to the unforeseen effects of it’s implementation, there have got to be at least 100 examples of the application of algorithms that are making our world tick more effectively every day, like the encryptions needed for secure daily electronic transactions, the design of advanced composite materials and improved aerodynamics for more fuel-efficient cars, optimized telecommunications routing, the analysis of disease genetics, molecular drug design, trip, traffic and shipment routing, computer game design, even the algorithm that apportions the number of U.S. Representatives based on census data.

In other words, smart people writing creative algorithms are the guts and magic that glue together much of the wonder and advancement in our modern life. And while it’s relatively easy to find and get freaked out by isolated examples of algorithms gone haywire, it’s also just as easy to overlook the vast numbers of unseen algorithms powering our world.

And yet, Wakefield somehow makes this seem like a sinister conspiracy, as if algorithms were secretly sentient beings slowly insinuating themselves into our lives in anticipation of the day they rise up and throw down their human overlords. Instead, algorithms are the application of great math in modern technology to help solve problems we wouldn’t otherwise be able to solve. When an algorithm goes wrong in some unanticipated way, it might be amusing, it might be quite serious (e.g. the Flash Crash), but it’s not really a signifier of anything more significant than a program with a bug. Of course, the higher the stakes (e.g., algorithmic trading systems that interact with one another and can move the market as a whole) the more important it is that we’re thoroughly testing and deeply thinking through the algorithms we implement. No systems, human or technological, ever operate without error, and there’s probably a strong argument that our algorithmically based systems operate with many fewer errors than human-controlled systems do.

The challenge, however, is that as humans we’re much more tolerant of human-based errors than we ever are of machine-based ones, even if those machines make far fewer errors. For example, take Google’s driverless car project. These prototypes are now out and running with astounding levels safety and accuracy. And indeed, this is actually the point of the program itself, to avoid the huge number of human-caused auto deaths and save millions of lives every year (this is the number one cause of death of young people) by relying on machines who can react and make these types of decisions much more quickly and accurately than any human. But just one human death by a failure of one algorithm in one car could kill the whole program. Is this logical if the program is saving many more net lives per year? No, but the illusion of human control and superiority is a powerful one.

In reality, however, where we get the most benefit is not from either human or algorithmic control—it’s in the combination of the two. It’s humans figuring out how and when and where and what algorithms to apply in new and creative ways to better our lives. It’s humans acting as a backstop to ensure algorithms are doing their jobs accurately, and catching the instances that require a lifetime of human experience, context and subtlety to truly understand. It’s why there will always be stock trades made by humans as well as machines. In fact, we employ these algorithmic backstops everyday at FirstRain. For example, we have incredibly sophisticated text analytics algorithms that analyze the Business Web content we find, look for a category in our taxonomy to apply to a given article, and if it doesn’t find one sufficiently descriptive, then suggests a new category to create. On the whole, this works incredibly well, and it’s why our taxonomy is so unbelievably granular. But even still, we need to have a team in place that reviews these algorithmic suggestions and can do a human sanity check, lest a “#CharlieSheen” occasionally slips in unnoticed.

Algorithms are tools, and in the end, it’s the use of tools that make us fundamentally human. This is probably why I’m not overly worried about the implications of humans now using the Web to supplement our memories. From the beginning of time, our bodies have evolved along with the technologies we’ve developed to survive and thrive. I’m sure there was handwringing about the loss of body hair as we began to wear clothes, and doomsday projections as our jaw muscles shrank thanks to our use of fire to cook meat. We’re the animals that use tools more than any other, and those tools change us the more we use them. And so as we employ these newest tools, these algorithms, into our daily life in a million new and groundbreaking ways, let’s be sure we’re thoughtful about those implementations, and creative, and far-sighted, and humble, and maybe even a little grateful.

[Stay tuned for Part 2 next week, by my colleague David Cooke, on the big implications of algorithms in enabling ‘just-in-time’ content delivery]

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