A peek into a typical workday: AI and thereafter
My workday begins at 8 am. I am seated at my desk, studying 2 screens my artificial intelligence (AI) powered assistant “Ripley” has tabulated and projected before me. Ripley is one among the several personalized AI aides available to everybody via neural implants, assisting us in both our personal lives and careers akin to the smartphone of yesteryears. The first screen shows 30 young faces along with their names and backgrounds. Adjacent to each face is a variety of data, most of it in the form of metrics and graphs. I carefully scan this information, which gives me insight into the academic history of each student of the undergraduate classroom in mechanical engineering I will be teaching in the next one hour. Ripley also runs me through collective data pertaining to the knowledge background, motivational levels and familiarity of the class regarding the contents of the lesson. The interface is easy to use, and I skim through the contents asking Ripley to provide more details whenever necessary. The second screen furnishes me with aims, learning outcomes, activities and assessments on the topic to be taught i.e. 3-D printing. These were generated by Ripley via machine learning algorithms corresponding to the information gathered in the first screen, and further tapping into big data available on the course from classrooms around the world. Before moving to the smart classroom1 I make some minor modifications on the lesson plan, which Ripley seamlessly communicates to the students’ AI assistants.
Once the students are seated, I begin the class by getting them to introduce themselves and going through the lesson plan. Those who cannot attend class physically join as remote participants via holoportation2, a virtual teleportation technology which enables full 3-dimensional telepresence. As the class progresses, I deploy AI enabled Augmented Reality3 interfaces to showcase several types of 3-D printers in real time. This helps students visualize their working principles as if they were in an actual workshop, the graphics near realistic, being generated by deep learning algorithms. In addition, students can manipulate and interact with the environment seamlessly via Ambient intelligence (AmI)4 systems. Assessments and task-oriented learning scenarios are simulated using Virtual Reality (VR), which enables students to design and manufacture components on virtual 3-D printers, and then validate its usage in an AI generated environment. My role during this time is to help facilitate learning by helping them explore and learn at their own pace, making use of the technology available at their disposal. I move around the classroom clarifying doubts, getting them to collaborate with one another and encouraging them to exercise their creativity in solving problems posed to them by their intelligent assistants. This is how I envision my typical workday to pan out, as a teacher of mechanical engineering in an era propelled by advancements in artificial intelligence and its progeny.
The changing face of higher education: en route to an AI era
Higher education in engineering and most other disciplines relies on an age-old knowledge-intensive approach, which rests on the foundations of rote learning and conformity. This has resulted in the mass-production of graduates lacking in vital attributes such as critical thinking, problem solving and decision making. Even though present-day education is aided by a variety of technological advancements ranging from computers to the World Wide Web, university graduates remain woefully short of skills necessary to succeed in the real world5. Needless to say, this necessitates significant transformations in the prevailing education system and its deliverers, especially if we are to remain “relevant” moving into an era dominated by machines and technology. Now, there are a few key questions which we must ask ourselves before formulating or attempting to establish reforms. Firstly, what are the principal attributes required in a workforce hired during a time when AI becomes ubiquitous? Secondly, what are the challenges faced by educators today in bringing about the changes necessary to build these skills? Finally, how can educators address these challenges and continue to do so in the future, without being replaced by AI themselves? I would like to examine the first two questions in this section of the essay and dedicate the last section to scrutinizing the final one.
With rapid advances being made in AI research as well as its growing ability to tackle tremendous quantities of information, graduates will no longer be hired based on the knowledge they possess, but their ability to apply this knowledge in solving complex problems6. Knowledge per se will be rendered useless in the future employee. To remain competitive in a world overshadowed by AI, humanity will need to train itself to perform “non-routine creative work” as opposed to “routine knowledge-based work”6. Artificial neural-network based AI systems have already mastered and replaced humans in a variety of specialized tasks in sectors including financial trading, transportation and healthcare diagnostics to name a few7. It is only a matter of time before they eliminate all repetitive task jobs, with automation substituting for manual labor in these cases8. Nevertheless, on the positive side, such an era is also believed to create a whole new sub-set of jobs and problems, comparable to that of a second industrial revolution9. These jobs engendered by AI and its sister technologies will require complex cognitive skills such as problem solving, innovation, creativity, workplace collaboration, self-direction etc.
Before we look into the process of building said skills, it is important that we are also aware of the key challenges currently faced by educators in administering their duties. Teaching is one among the most overworked and underpaid careers of today, with high attrition rates, demanding workloads as well as poor work-life balance10,11. Teachers face a plethora of challenges when carrying out their tasks such as lack of sufficient time, lack of student engagement, lack of funds and resources, inadequate training etc. The current system forces them to be more concerned about covering the curriculum, when they should in fact be focusing on achieving the learning outcomes of the lesson. Consequently, they adopt a vapid lecture-based approach for imparting knowledge to students, which rarely allows for interaction and at the same time is boring12 thanks to the enormous amounts of information doled out in short periods of time. Another key issue is the dearth of training given to teachers in adapting themselves to the changing needs of time, both in terms of engaging students as well as harnessing technology to promote deeper learning and better retention levels. Next, there exists a disparity in the distribution of learning resources among students, which prevents educators from achieving equal educational outcomes. This is a consequence of the inequities existing among the different communities in terms of gender bias, social class and economic status. Only a privileged few can afford or have access to technology, facilities, qualified and experienced teachers necessary for a well-rounded education, thus giving rise to educational inequality and elitism13.
Educators are further handicapped by the diverse learning styles of students and as a result, deploy teaching techniques which are general in nature, assuming that it caters to the majority. Sir Ken Robinson, one of the most illustrious figures in education today, has stressed on the need for more personalization and less standardization in learning14. Standardization in education has worked well in the 20th century where most jobs have required graduates to specialize in narrow domains, rarely needing them to think out of the box. It has further influenced teachers and management in their approach to education, creating a culture where traits like innovation and creativity are almost non-existent. On the contrary, the 21st century calls for an education system which goes beyond mere dissemination of knowledge; it calls for a system which empowers its products to remain productive and evolve into successful individuals once they step outside its portals.
The way forward for educators: what will it take?
Now, how do we ensure this idea of an efficacious education system is made tangible going forward into an AI era– or to be more precise, what efforts will it take to realize this goal of building a relevant skill set in every student, irrespective of their socioeconomic status or academic discipline? I argue that the answer to these questions rests on remolding the three fundamental aspects of educational delivery: the “what” is delivered, the “who” delivers and the “how” to deliver.
The “what” and the “how” for the most part depends on the skillset to be forged into the workforce. At this year’s World Economic Forum Annual Meeting held at Davos, several leaders including Jack Ma, founder of Alibaba Group emphasized the importance of soft skills like independent thinking, values and team-work to stay competent in a future where all routine work is automated via AI15. For this to materialize, the current knowledge-intensive approach to education must be overhauled and in its place, a problem-based learning platform16 must be instituted into the curriculum. The principle of this approach is to allow students to learn and understand concepts by solving open-ended real-world problems in collaborative groups. In essence, the curriculum is designed so as to “nurture” creativity, not “smother” it. Several universities including Stanford and St. Gallen have already implemented this approach in the form of courses such as Design Thinking, where industrial partners put forward problems in class, which students then attempt to resolve guided by their professors in a highly engaged manner over long periods of time6. This fosters active learning among students, allowing them to assume responsibility in the learning process, and providing them with opportunities to exercise their creative skills while working together as a team. Moreover, this helps them gain a broader picture of the problem, which is important to help them function as effective leaders and managers who can look beyond their own specific domains in an industry or organization.
AI powered technologies can further be harnessed to augment the “how” to deliver aspect in several inventive ways. For example, if the class was on 3-D printing, AI powered augmented-reality (AR) interfaces could be utilized to simulate virtual printers, which students can then utilize to print out virtual models of the components in real time. Such a virtual set-up gives them the freedom to make mistakes and rework their solutions, as there is no material cost or waste involved. In addition, this allows students to attain higher levels of learning as they learn concepts in a setting closely resembling their future context, which in this case is a 3-D printing firm. Assessments can be done on the fly, with AI assistants being harnessed to provide every student with immediate feedback. AI powered Virtual Reality (VR) interfaces on the other hand can be used to simulate customized field trips making it possible for each student to have a personalized learning experience. These are typical examples of an adaptive learning system where data collected on students’ performance can then be leveraged by AI to provide learning content tailored for each of them17.
The “who” delivers includes educators, administrators and policymakers, on whose shoulders lies the responsibility of bringing about the educational reforms necessary for preparing humanity to stay competent in an AI era. I believe that the initial target to transformation at any level of education should be the educators themselves. Adequate training should be given to both existing and future educators to implement the revamped competency-based curriculum and harness the technological advances to promote deeper learning among students. It is vital that as teachers, we do not end up competing with AI systems like “Ripley” for imparting education; instead we should focus on using such intelligence assistants as enablers in helping students achieve the learning outcomes, and in delivering an enjoyable and stimulating learning experience. For us educators to stay ahead of AI, we must learn to cultivate social and emotional skills in engaging students, as this is what differentiates us from the former. We must redefine our traditional role of solely being a deliverer of knowledge, to that of an empathetic and effective facilitator of the learning process18. In addition, funds must be directed to make educational technology affordable and accessible to all irrespective of their backgrounds, so that going forward we do not end up recreating an automated version of the existing inequities in education.
In conclusion, I firmly believe that the influence of AI on education is inevitable; and only by embracing the former can we steer it towards rising to a new level of empowerment and ephemeralization19 in any discipline, be it engineering or otherwise.
- Alelaiwi, A. et al. Enhanced engineering education using smart class environment. Comput. Human Behav. 51, 852–856 (2015).
- Fanello, S. et al. Holoportation : Virtual 3D Teleportation in Real-time. Chi 741–754 (2016). doi:10.1145/2984511.2984517
- Billinghurst, M. Augmented Reality and Education. New Horizons Learn. 21(3) 195-209 (2002). doi:10.4018/jgcms.2011010108
- Remagnino, P. & Foresti, G. L. Ambient intelligence: A new multidisciplinary paradigm. IEEE Trans. Syst. Man, Cybern. Part ASystems Humans. 35, 1–6 (2005).
- Nair, C. S., Patil, A. & Mertova, P. Re-engineering graduate skills – a case study. Eur. J. Eng. Educ. 34, 131–139 (2009).
- Bernhard Schindlholzer. Artificial intelligence & the future of education systems | Bernhard Schindlholzer | TEDxFHKufstein – YouTube. Available at: https://www.youtube.com/watch?v=ZdHhs-I9FVo. (Accessed: 26th January 2018)
- Tegmark, M. Life 3.0 : being human in the age of artificial intelligence.
- Frey, C. & Osborne, M. The future of emplyment: how susceptible are jobs to computerization? Sept 1–72 (2013). doi:10.1016/j.techfore.2016.08.019
- Kevin Kelly: How AI can bring on a second Industrial Revolution | TED Talk | TED.com. Available at: https://www.ted.com/talks/kevin_kelly_how_ai_can_bring_on_a_second_industrial_revolution. (Accessed: 27th January 2018)
- Teachers are overworked but still dedicated, new survey suggests | Teacher Network | The Guardian. Available at: https://www.theguardian.com/teacher-network/2015/mar/12/teachers-overworked-undervalued-education-survey. (Accessed: 26th January 2018)
- 60-hour weeks and unrealistic targets: teachers’ working lives uncovered | Teacher Network | The Guardian. Available at: https://www.theguardian.com/teacher-network/datablog/2016/mar/22/60-hour-weeks-and-unrealistic-targets-teachers-working-lives-uncovered. (Accessed: 26th January 2018)
- Why do 60% of students find their lectures boring? | Education | The Guardian. Available at: https://www.theguardian.com/education/2009/may/12/university-teaching. (Accessed: 28th January 2018)
- Educational inequality still an obstacle to talented students, Letters in Print News & Top Stories – The Straits Times. Available at: http://www.straitstimes.com/forum/letters-in-print/educational-inequality-still-an-obstacle-to-talented-students. (Accessed: 28th January 2018)
- Ken Robinson: Bring on the learning revolution! | TED Talk | TED.com. Available at: https://www.ted.com/talks/sir_ken_robinson_bring_on_the_revolution. (Accessed: 26th January 2018)
- 6 quotes from Davos on the future of education | World Economic Forum. Available at: https://www.weforum.org/agenda/2018/01/top-quotes-from-davos-on-the-future-of-education/. (Accessed: 30th January 2018)
- Schmidt, H. G., Rotgans, J. I. & Yew, E. H. J. The process of problem-based learning: what works and why. Med. Educ. 45, 792–806 (2011).
- Three ways education is being disrupted by digital technology. Available at: https://www.digitalpulse.pwc.com.au/three-ways-education-disruption-digital-technology/. (Accessed: 31st January 2018)
- These 7 trends are shaping personalized learning | Education Dive. Available at: https://www.educationdive.com/news/these-7-trends-are-shaping-personalized-learning/434575/. (Accessed: 1st February 2018)
- Ephemeralization – Wikipedia. Available at: https://en.wikipedia.org/wiki/Ephemeralization. (Accessed: 1st February 2018)