The traditional education system is currently at a turning point. Driving forces such as novel digital tools and a change in student needs are putting the market in the perfect position to be disrupted. For example, the current job market is extremely competitive, causing a demand for more specific skills. This is resulting in an increased demand for information and education on topics such as technology and engineering (Frey, 2013). In addition, the cost of traditional education is at an all-time high.

A logical response to these developments is the upsurge of cheaper, modern and more accessible forms of learning. Edtech companies such as CodeAcademy, Lynda.com and Pearson (eText) are already filling education gaps, by offering courses and other learning materials online, often for free (Lynch, 2018). I expect online learning platforms to become the norm in the future, providing people with the opportunity to study preferred content, available on-demand at their own time and place. This goes hand in hand with the increase of self-directed education, entailing that individuals will be able to choose more specifically what they want to learn more about and how. Other innovations such as augmented reality and games will most likely also play a role in this, as alternative and possibly more reliable methods for assessment and learning (Pozo-Olano, 2018).

Like many other social systems, the education system is built on trust, or better yet, on a certain belief. For example, the functioning and offerings of traditional educational institutions are based on the premise that if you commit to and complete a program, you earn credits. Afterwards, you can use these credits to certify yourself in the job market and rely on them to find a job. But what if we came up with new credentialing systems? Then, a traditional university degree would lose most of its value. If this were to happen in combination with the abovementioned developments, the scope of education would change completely and educational institutions as we know them might become obsolete.

I believe that the transformation of the education industry would be a positive development, as it would ultimately increase equal opportunities as it will give more people access to affordable education. I also think the change is necessary in order to be able to compete in the current job market. What do you think the future of education looks like? Do you think universities will ultimately cease to exist?

Sources:

• 6 edtech companies that are disrupting higher education
• By 2030 over 50% of Colleges will Collapse
• 9 Things That Will Shape The Future Of Education: What Learning Will Look Like In 20 Years
• A Year of Disruption? 7 Education Trends for 2018

Due to the digital revolution, algorithms are becoming increasingly interwoven into practically every aspect of our lives. Not humans, but mathematical models are currently deciding which school you will attend, whether or not you will get hired for a job, the level of your insurance cost and whether or not you will be granted a loan. Currently, these models are even being used to decide if offenders are eligible for parole (O’Neil, 2016).

When you hear someone talking about algorithmic decision-making, you will likely hear them use the words ‘objective’, ‘neutral’, or ‘fair’. Indeed, algorithms are generally perceived as fair tools that are more objective decision-makers than us biased humans. In some cases, this is true. For example, an algorithm is never tired, never has a bad day and will not favor a candidate because he or she is similar to itself. However, the question is if we are not blindly trusting these techniques too much. After all, they are always based on human input. Even the most advanced algorithmic techniques that are able to self-improve by implementing deep-learning methods are ultimately based on previous and current human practices. If these were biased, then so is the mathematical model (Eder, 2018).

The problem is that algorithmic bias is difficult to detect, as the underlying processes are often too complex to understand or interpret. A more serious challenge is that many parties involved do not seem to be actively researching, evaluating or decreasing algorithmic bias at all (Knight, 2017). This might also be caused by extremely low awareness of this issue.

As AI becomes even more prevalent in modern life, the urgency of this societal issue increases. Considering the magnitude of the impact of this problem, it is essential that we stay critical of new technological developments so that we can try to eliminate algorithmic bias in the future.

The above mentioned problem is very clearly explained by Catherine O’Neil in her book: ‘Weapons of Math Destruction’.

Sources and recommendations for further reading:

Biased Algorithms are Everywhere, and no one seems to Care

How Can We Eliminate Bias In Our Algorithms?