Skip to content

The algorithms that rule our lives

Algorithms sound somewhat mysterious and complex. By definition, however, algorithms are basically a sequence of steps or activities, often directed toward solving a problem. The steps to solving a problem may be simple (how to bake a pizza or tie your shoes) or complicated (returning web search results based on an input term or recommending who you should follow on a social networking site). Jacques Ellul warned of the dangers of technique, and by extension technology, as a means to force humanity into states of conformity. No where is this more true than with algorithms. Google’s CEO recognizes the power of algorithms, offering a chilling and prophetic insight into the future role of search engines: “I actually think most people don’t want Google to answer their questions. They want Google to tell them what they should be doing next”.

Globe and Mail’s article on Programming our Lives Away reviews the growing dominance of algorithms in our lives

Increasingly, algorithms are used to determine whether we can get access to credit, insurance and government services. They are posing a challenge to human decision-making in the arts. They are being used by prospective employers to decide if we should be hired. They can determine whether your online business will succeed or fail, and they have revolutionized the world of high finance…
Some companies now use algorithms to make decisions around hiring and firing. At Google, which boasts that “almost every [personnel] decision is based on quantitative analysis,” engineers have developed an algorithm to identify those employees most likely to leave to work for a competitor or strike out on their own. Employee surveys, peer reviews, evaluations, promotion and pay histories feed into the algorithm. It helps us “get inside people’s heads even before they know they might leave,” a Google manager told The Wall Street Journal last year.
At IBM, programmers put together mathematical models of 50,000 of the company’s tech consultants. They crunched massive amounts of data on them – how many e-mails they sent, who got them, who read the documents they wrote – and used this information to help assess the employees’ effectiveness and deploy their skills in the most cost-efficient way.

I’m interested in data analysis and algorithms because of the huge potential for learning analytics to give educators, organizations, and learners better insight into the learning process. Given this interest, at TEKRI we are co-organizing and hosting the upcoming Learning Analytics Conference (Banff, Feb 28-March1, 2011), and I’ll be presenting on the topic of learning analytics December 3 (online) with the Connect@NMC. But huge questions remain as to the appropriate role of analytics to do what is often managed through social interactions – i.e. personalization and adaptivity of learning and content. A significant difficulty that learning analytics needs to address is the possible return to behaviourism where we make decisions about learning only on observable behaviours of learners. Nonetheless, algorithms define our lives and how organizations interact with us. It’s a data-driven world, and the algorithm reigns supreme.


  1. Hello again…
    I have been thinking about how an algorithm would work in formal education. I think it would be a powerful one if we could use an algorithm to create an “individualized learning platform”. To learn more about this concept just check out the vision developed by the ‘School of One’, NYC Department of Education.

    I am grappling as to how we could apply this to a formal school? How many teachers would we need to structure the learning and monitor student progress?

    Saturday, November 27, 2010 at 3:52 pm | Permalink
  2. Algorithms in Education have been the wet dream of many since Skinner. Algorithms are discovered by the professionals of a domain, and not by those who want to spread the use of algorithms for the sake of algorithms (aka “technology in education”).

    By the way, and by definition, algorithms operate only on data. Baking a pizza or tying my shoelaces can never be perfomed by algorithms – only symbolic representations of these activities may be performed by algorithms. Flour cannot be dealt with by algorithms.
    Monitoring learning by data about learning may be performed by an algorithm, but first such an algorithm has to be discovered, not to be invented and fetched like the first programmers of “teaching software” did in the 60s.

    Sunday, November 28, 2010 at 12:35 pm | Permalink
  3. Fascinating post on algorithms. Never really thought of them past trying to guess at Google algorithms for maximizing our school’s Search Engine Rankings.

    I’ll never look at typing my shoes the same way.

    Sunday, November 28, 2010 at 1:54 pm | Permalink
  4. DolorsCapdet wrote:

    The advantage we have is that all algorritmos are programmed by humans. This means that they can give them the necessary autonomy for each case. Therefore, would be equally valid for a return to behaviorism or as an evolution of connectivism :) .

    Sunday, November 28, 2010 at 4:43 pm | Permalink
  5. Howard wrote:

    Hi George;
    I think you raise valid concerns. Algorithms are tools and if the person behind the tool does not understand it, and is not cognizant of its limits, it will not serve its intended purpose as well as it should. Many of your examples combine measurements within the algorithm adding layers of complexity, but at heart, I think they are only a tool to extend our thinking not as a substitute for it.

    Sunday, November 28, 2010 at 10:17 pm | Permalink