A Transitioning Into The Age of A.I. — Education In A New Lens
Intro

If you’re like me, you love the idea of change, especially when it involves less monotony and more time for creativity. As a developer, I especially anticipate artificial intelligence — and in particular machine learning — as an agent for that type of change on a large scale in the near future. It has the ability to take what we already have (data and resources) and use them to create optimal systems, thereby freeing up humans for what we do best: socialize, collaborate, and dream.

The prospect of nearly zero “boring” or monotonous jobs, however, can be intimidating. They are the entry level stepping stones for success, and in some cases the only option for the under-educated and the disabled. Could the emergence of Big Data and machine learning create an uncrossable divide between those lucky enough to still have jobs and those outdated? In this article, we’ll address this question and propose a solution. AI is not going anywhere — escape isn’t an option. Instead, it’s an opportunity to change by allowing the education system to evolve with our economy.

A Few Notes

The information found in this paper is all scholarly, annotated via numbers in [brackets]. A bibliography can be found at the bottom for reference.

I was originally inspired to write this essay by the YouTube original series, The Age of A.I. I highly recommend it to anyone interested. It has no technical jargon, and gives a broad overview of the state of AI today, as well as where it could be in the near future.

Artificial Intelligence: What Is It?

Everywhere we look, industries are transformed by artificial intelligence. While typically associated with analytics, AI does much more, from driving cars to predicting disease in patients. [1] On the other end of the spectrum, popular belief has made it closer to science fiction, able to predict any action, build anything, or destroy the human race. But what is it, exactly?

The Merriam Webster dictionary defines AI broadly: the capability of a machine to imitate intelligent human behavior. [2] Depending on how you interpret this, anything could have artificial intelligence, maybe even a toaster. As technology progressed, however, the interpretation of this definition has changed. Toasting bread, while essentially a human endeavor, is not considered a branch of AI by today’s standards. For the purposes of this paper, I will further define AI as a program or machine dynamically acting based on the information it has and whatever goal(s) it has been given. So, from my definition of artificial intelligence, a toaster is not AI, but if it could automatically toast me bread every morning I don’t have an appointment scheduled before 8 AM, it might be.

The toaster idea may seem comical, but artificial intelligence is no joke. According to the Wall Street Journal, AI will have increased the world’s economic output by at least 14% in 2030, which scales to approximately 1.2% in annual increase. To put that into perspective, the invention of steam engines in the 1800s increased the world’s annual economic output by 0.3%. [3] On a scarier note, according to a study by economist Frey Osborne in 2013, approximately 47% of US jobs were at a high risk of being replaced by machines in the following twenty years. [6]

AI is already affecting the world today. And not just in the workplace, either. Personal assistants like Siri and Alexa are common examples. Netflix uses AI to determine which movies you are suggested. [4] It’s used to accurately predict pizza orders by some restaurants. [7] AI’s affected nearly every industry, so it begs the question: why have education and training hardly changed in the last century? AI for use in education (AIEd) has been in development for over thirty years and is still largely unrecognized. [5] I don’t know the answers for sure, but perhaps the recent Coronavirus pandemic will spur AIEd into more widespread use. But here I don’t want to focus on the past. We will instead dispel fear of the future. AI in education and training should be developed, invested in, and ultimately accepted. It’s what the next generation needs in order to thrive in an Age of Artificial Intelligence.

The Workplace

We’ve established that the growth of AI will soon eliminate many of today’s jobs. This means we’ll have a large population of unemployed people in the near future, particularly in first world countries where AI is incorporated earlier. This was the case even before the COVID-19 pandemic, but the process could be accelerated now that so many workers have been laid off and companies are forced to run with less human interaction. Unemployment hurts the economy, politics, and the individual. [8] GDP goes down, waste goes up. Governments borrow money to pay unemployment benefits, and handouts become political leverage. If nearly half the United States population became unemployed, any kind of benefits to their demographic would win massive votes. There is talk of AI necessitating a universal basic income. Billionaires Elon Musk, Bill Gates, Richard Branson, and Mark Zuckerberg expect some form of it to be necessary soon. [14] But economy and politics aside, unemployment is unhealthy for the individual. Studies show quality of life, proficiency in skills, and mental health can all be damaged by unemployment. Finally, there is a direct correlation between unemployment and crime rate. [8]

Historically, new tech creates new jobs, albeit removing others. [5, 7] But will this unemployed population be skilled enough to fill those new occupations? We can’t be sure, but from what we know AI can do, we can make some guesses.

AI excels in finding patterns and carrying out repetitive or ­predictable tasks. [7] It has a hard time with human connection and emotion. [5] And while an argument can be made that AI is creative in some senses, it is far from dominating the movie or music industry anytime soon. [7] According to the AIEd researchers at UCL Knowledge Lab [5], these new, so-called 21st century jobs will require:

In approximately ten years:

Jobs will require more cognitive ability than many of the current open occupations. Education will need to teach quickly and effectively, so the current workforce can transition into new, higher skill jobs. It will also need to develop learning habits and problem-solving skills. Education will not only give information but teach how to learn using available resources. These already huge resources will continue to grow with the internet.

Social skills will be more valuable, as AI will likely still struggle in this area. Education then should involve students in more collaborative projects where communication and relateability are fostered.

Adaptability is the new norm. New technologies will be presented faster than ever, and those able to take advantage of them will succeed. Training will need to find ways to teach adults new skills in ways they will understand. I will add, these systems should also consider their busier schedules and previous work experience.

Can artificial intelligence achieve all this in education and training? Evidence suggests it might bring us very close. On the other hand, human teachers probably won’t be replaced. As we’ll touch on soon, their roles will instead be enhanced and augmented. But before we go into that, I want to dispel a common myth of AI — it is inherently dangerous.

The Danger of Artificial Intelligence

There is a prevailing idea that believes at some point in the future AI will surpass human intelligence and either kill or enslave us. One such idea is that AI will eventually become sentient. It could then harm humanity out of self-preservation. Another is that AI may misinterpret a command to protect humanity, and instead micro-manage or enslave it. Several well-known minds are seriously concerned about the development of a general super-intelligence, commonly refereed to as the Singularity. Elon Musk firmly believes that AI will soon be more dangerous than nuclear warheads, [12] but there are also several authorities on the subject who find Elon’s views over the top. Mark Zuckerberg from Facebook and others [13] disagree with these “doomsday AI predictions” and think AI is worth the risks considering how it will improve our lives.

To understand the argument, we must know there are two divisions of artificial intelligence: general and specialized. Specialized AI is the most common; it’s designed to perform one type of task and usually takes advantage of a specific technology, for example object or speech recognition. These are incapable of truly “reasoning”, they simply apply algorithms such as machine learning to given information. General AI is designed to mimic a natural mind, in that it can apply itself to many kinds of tasks. [1] This area of AI is not anywhere near replicating a human’s mind. The best general AIs out there are basically a combination of many specialized AIs, and hence still do not have the ability to reason about their situation or identity. [7]

But what of machine learning? AI are simple now, but if they are constantly improving, they must inevitably surpass human intelligence, correct? This is a common misconception. Machine learning is a sub-field of artificial intelligence where a program finds patterns in data using either neural networks or some other similar algorithm. An algorithm must be “taught” patterns using data. In the case of object recognition, it may be presented with pictures of cars. At a certain point, the program would be able to identify cars in photos independently using patterns it noticed in previous data. Hence, the machine “learned” something. However, it only learned what the programmer enabled it to learn, which is limited to visual patterns. The same program could not be used to identify patterns in say, economics. A different machine might be built to assess patterns in economics, but no algorithm would have any framework in which to relate the results of these two machines, unless it were in some pre-programmed way. Hopefully, you are beginning to see how difficult it would be to recreate the human mind. Even if somehow a system was built to analyze data from all specific AI, it would not be able to make sense of it without a preprogrammed decision-making process. In other words, a human would really make the final decision. On top of all this, the categories we use to make specific AI (say speech recognition or finding patterns in economics) are human made. A true recreation of the mind would be able to decide on those categories itself, which no AI today or in the foreseeable future can do.

Before worrying whether AI will become more intelligent that humans, we should first try defining intelligence. If it is the ability to quickly find patterns or crunch numbers, computers have long since surpassed us. But the truth is, intelligence has many more dimensions. There are some areas computers excel in, and many others where humans will nearly always have the upper hand. [1]

That is not to say people can’t use AI in evil ways. Tools have always been as good as their users. The question of whether technology as a whole should advance isn’t the focus of this paper, although I will say most agree today’s world is better than the world of a few hundred years ago, regardless of all the ill-intentioned people along the way. Development of new tools is inevitable. AI is one of those tools. Will we use it for good or hesitate in fear while criminals use it for evil?

How AI Can Change The Way We Learn

We now have a more accurate idea of AI and its potential risks. The need for it in education and training is also apparent. Here are what I think are the biggest benefits to applying AIEd to schools, HR training, and even third world countries where quality education is limited.

Schools

Training the next generation to thrive in the age of AI will require more than what our current education system can offer. Referring to our three “21st century skills”, graduates will need higher cognitive ability, exceptional social and collaboration skills, and perhaps most importantly, the ability to learn and adapt to new technologies.

Personal tutoring is generally thought to be the most effective form of teaching. [5] With human teachers, this is simply not possible for every student. Classes generally range around thirty students. This means that special attention cannot normally be given to any one person. Unfortunately, this is one cause of what’s known as the Matthew Effect [5]; students with better educational backgrounds get more from the material, further widening the gap between high and low achieving students.

AI can provide students with Intelligent Tutoring Systems (ITS), which consider their current education, demographic, emotional state, and personality to give them the best tutoring experience possible. These ITS could be accessed from anywhere, being hosted online. They could suggest projects designed specifically for each student’s needs and provide more feedback than possible in a traditional classroom. Machine learning would be used to detect where students tend to get stuck in the material and how best to guide them based on all the other data it gathers. As these ITS help students at home, they would gather info on what each has learned, how they learned, and where they are still struggling. Back in the classroom, the teacher would be presented this information and given recommendations on how to curate the material based on the students’ needs. [5]

Aside from tutoring, AI could be used to improve collaborative projects. Using algorithms and machine learning, AI could match students together for the most productive team. Or, depending on the project’s goals, the AI may prioritize diverse groups to improve the students’ social and cultural skills. [5]

AI can also help moderate and guide group projects, a difficult task for just one teacher. Depending on how they are implemented, these AI could also help more accurately measure which students contributed to projects, thereby keeping them accountable. Anyone who has worked on a group project understands the need for an improvement in the grading system. [5]

AI in education will change the world. The sooner it is implemented, the more data and feedback developers will have. On top of this, when parents, teachers, and governments see the benefits of AIEd, funds for these developers will be easier to come by. AIEd can already provide education with most of these benefits to a certain degree, but it needs more support. The sooner the push for its use and development, the better. 21st century jobs won’t wait for our education system to catch up.

HR Training

Most of the benefits to schools also apply to training in the workplace. But since AI, and particularly machine learning, is improved by data, I would argue it could be even more effective in these settings. Adults in the workplace have more experience and history. AIEd could take this into account, and instead of giving the same training to each employee, time could be saved by only teaching them what they do not already know.

Companies big enough to employ AI in their training would likely also have massive data related to their respective fields. As virtual reality becomes more commonplace in training, AI could use this data to create plausible virtual situations. These scenarios might feature virtual characters which respond based on data from previous real-life field data.

AI in training will be necessary to smoothly transition into a world of more skilled jobs. If there will be a universal basic income, companies should recognize they could very well be the ones paying for it. AI will be utilized by companies to increase efficiency, as it should. But those who benefit from AI should also use it to employ and train others in new ways. Otherwise, companies could end up paying people’s wages without receiving the benefits of their labor.

Third-World Countries

AI will never replace human teachers, but there are many places where there simply are not enough teachers to educate every child. In fact, the world would need approximately 25.8 million more teachers to give every child a primary education by 2030. [5] In the short term, AIEd could be deployed in poor areas along with cheap online educational material. Much like the Matthew Effect in the classroom, technology is widening the gap between first and third world nations. AIEd can help keep the lagging countries up to speed.

How effectively these technologies can be used in developing countries will vary. Currently, 81% of people in first world countries have access to the internet. About 40% have access in third world countries, and only 15% in the least developed countries. At the same time, though, 95% of the world’s population has access to cellular data. [10] A push may first need to be made in some areas to provide children with devices and funds to afford data for them. Then AIEd can be used to give students personal tutors. These could even help them learn the basics of “internet literacy”, such as keeping information private and using security software.

There are already plenty of organizations reaching out to underprivileged children. ITS systems only need a device connected to the internet; they could easily be integrated into their programs. AIEd can and should be used to empower those unlucky enough to be born into poverty.

The Ethics of Artificial Intelligence

The benefits of AI in education and training are clear, and as datasets grow and models are improved, they’ll only get better. But for these systems to give such personalized service, personal data will be needed. Basic information like names and ages, yes; but also more nuanced things. For example, to detect a person’s emotional state (which can be used to improve their experience) eye patterns might be captured by camera. Is it morally acceptable to record these data? At any rate, I believe participants should have the right to opt out of any type of data recording. The experience may be worse as a result, and the AI’s datasets maynot grow as quickly, but we have a moral obligation to protect others’ privacy.

The internet today does not respect anyone’s privacy. It is the nature of an open network; no one government or person can control it. If we are to increasingly harness it to provide educate others, then, a basic “internet literacy” should be taught. While the opportunities of the internet are extraordinary, it has also opened more avenues through which crime and illegal content can thrive. [10] If education is moving into the digital world, everyone should be aware of the risks. Identity protection and cybersecurity should be implemented into our education systems and our company’s training programs.

While there are ethical questions to be asked about using AI in education and training, I would make an ethical argument in favor of AIEd. Artificial intelligence is the very reason jobs will be so difficult to find for the next generation. Therefore, companies and governments who have benefited so much from it should use AI to raise a generation of skilled workers who can find careers in new areas.

Conclusion

The world is changing, I would say for the better. But if we are to transition, the race between technology and education needs to end. Jobs will soon require more intelligence, social skills, and adaptability than ever. With AI, a smooth transition could be achievable. It’s not technology versus education. It’s education empowered by technology. I hope this paper has inspired you to embrace AIEd, however that may be. Unfortunately, adopting AIEd is not as simple as it could be. It’s still a cottage industry, and as such what it really needs is investors, developers, and educators. If you are one of these, or would like to learn more, I’d highly recommend reading Pearson’s comprehensive paper, Intelligence Unleashed: An Argument for AI in Education. [5] It goes into much greater detail, and points out specific areas that need advancement before this tech can be widely integrated.

Artificial Intelligence will remove jobs, but that doesn’t mean unemployment must go up. Let’s be sure the Age of AI isn’t just a more efficient age, but a happier one, too.

Bibliography

1. Marr, B. (n.d.) 5 Myths About Artificial Intelligence (AI) You Must Stop Believing. Bernard Marr & Co. Retrieved from https://bernardmarr.com/default.asp?contentID=1192

2. artificial intelligence. (n.d.) In Merriam-Webster.com dictionary. Retrieved from https://www.merriam-webster.com/dictionary/artificial%20intelligence

3. Berger, I. W. (2018, Nov 16). The Impact of Artificial Intelligence on the World Economy. The Wall Street Journal. https://blogs.wsj.com/cio/2018/11/16/the-impact-of-artificial-intelligence-on-the-world-economy/

4. Machine Learning. (n.d.). Netflix Research. Retrieved from https://research.netflix.com/research-area/machine-learning

5. Luckin, R., Holmes, W., Griffiths, M. & Forcier, L. B. (2016). Intelligence Unleashed. An argument for AI in Education. London: Pearson.

6. Frey, C. B., Osborne, M. A. (2013). The future of employment: How susceptible are jobs to computerisation.

7. Foley, S., Motskin, Y., Ford, E., Lanier, C., Lesinski, T., Gertz, P., and Murray, D. (Producers) & Zylstra, N., Roth, I., Stier, L. (Directors) (2020) The Age of A.I. Retrieved from https://www.youtube.com/playlist?list=PLjq6DwYksrzz_fsWIpPcf6V7p2RNAneKc

8. Simpson, S. D. (2020, April 15th) The Cost of Unemployment to the Economy. Retrieved from https://www.investopedia.com/financial-edge/0811/the-cost-of-unemployment-to-the-economy.aspx

9. BasuMallik, C. (2018, Nov 20) 3 Incredible Ways AI Will Transform Learning and Development. Retrieved from https://www.hrtechnologist.com/articles/learning-development/3-ways-ai-will-transform-learning-and-development

10. ICT Facts and Figures 2016. (2016) Retrieved from https://www.itu.int/en/ITU-D/Statistics/Documents/facts/ICTFactsFigures2016.pdf

11. Children in a Digital World. (2017) Retrieved from https://www.unicef.org/publications/files/SOWC_2017_ENG_WEB.pdf

12. Catherine, C. (2018, March 14) Elon Musk: ‘Mark my words — A.I. is far more dangerous than nukes’ Retrieved from https://www.cnbc.com/2018/03/13/elon-musk-at-sxsw-a-i-is-more-dangerous-than-nuclear-weapons.html

13. Catherine, C. (2017, July 24) Facebook CEO Mark Zuckerberg: Elon Musk’s doomsday AI predictions are ‘pretty irresponsible’ Retrieved from https://www.cnbc.com/2017/07/24/mark-zuckerberg-elon-musks-doomsday-ai-predictions-are-irresponsible.html

14. Catherine, C. (2018, February 20) Billionaire Richard Branson: A.I. is going to eliminate jobs and free cash handouts will be necessary. Retrieved from https://www.cnbc.com/2018/02/20/richard-branson-a-i-will-make-universal-basic-income-necessary.html
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['Artificial Intelligence', 'HR', 'Education']