Automation, algorithms and artificial intelligence: New ways of learning in the workplace
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The document discusses how automation, algorithms, and artificial intelligence will change workplace learning in the future. It outlines four phases of the industrial revolution and notes we are currently in the third phase of digital transformation. New technologies like AI, blockchain, VR, and data analytics will augment jobs, automate some tasks, and create new roles. Organizations must help employees continuously learn and adapt through flexible, lifelong learning strategies to prepare for permanent change. The future of work will require workers to learn, unlearn, and relearn skills throughout their careers.
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Automation, algorithms and artificial intelligence: New ways of learning in the workplace
- 1. Automation, algorithms and artificial intelligence: New ways of learning in the workplace © VIR LEARNING 2018
- 2. A learning and development consultancy which helps HR professionals understand and apply research into the digital potential /vɪə/ © VIR LEARNING 2018
- 3. James Whitelock • Founder and MD at ThinkInCircles.com • Think In Circles is an award-winning digital strategy agency that provides services to recruitment and HR • Formerly a cross marketing/IT specialist for Vedior, Ranstad and Empresaria @jamescwhitelock © VIR LEARNING 2018
- 4. Dr. Robert Farrow • Research Fellow in Institute of Educational Technology at The Open University (UK) • Technologist and philosopher; education researcher • Fellow of the Higher Education Academy • Research consultant for organizations including higher education providers; NGOs; business & voluntary sectors @philosopher1978 © VIR LEARNING 2018
- 5. The learning landscape © VIR LEARNING 2018
- 6. Challenges in workplace learning • Is training the same as learning? • Are we sufficiently proactive, or just responding to what is minimally required? • Do we think enough about how people learn? • Does everyone learn in the same way? © VIR LEARNING 2018
- 7. Four phases of industrial revolution • 1st – 1700s-1800s – industrial manufacturing; steam power; rural depopulation • 2nd – late 1800s-WW1 – expansion of industry; mass production; electrification; communication technologies; internal combustion engine • 3rd – 1980s-present – information and communication technologies; computing & ICT; automation • 4th – ‘Industry 4.0’ – cyber-physical systems; biotech; cloud computing; artificial intelligence; information transparency; digitalisation; integration of existing systems © VIR LEARNING 2018
- 9. “Industry 4.0” CC-BY-SA Olga Tarkovskiy.
- 10. Amara’s law We tend to overestimate the effect of a technology in the short run and underestimate the effect in the long run. © VIR LEARNING 2018
- 11. Industry 4.0 - workplace of the future • Automation: new tech will change some jobs and create new ones • Requalification: support job transitions • Flexibility: agile approaches to learning & development • Lifelong learning: need to continuously learn & develop • Transversal skills: soft skills; skill reusability; people skills; communication • Improved digital skills: for both industry and to access learning • Creativity: humans focusing on what machines cannot do © VIR LEARNING 2018
- 12. Workplace implications • Global Human Capital Report (2017) suggests the world has only developed 62% of human capital • Low confidence of global CEOs in their own company readiness for digital activities: “The confidence in their organizations’ digital abilities is at an all-time low: Just over half rate their Digital IQ as strong or very strong (a score of 70% or greater), down from two-thirds of executives in 2014 and 2015” (Curran et al., 2017) • Getting technology enhanced learning right is essential for the challenges of the future © VIR LEARNING 2018
- 13. Workplace implications • Enhanced learning and development strategies will be an increasingly important part of the workplace of the future • Businesses need to adapt to a process of permanent change with increases in staff turnover and a general drop in market certainties • Understanding which technologies can enhance l&d strategy is vital © VIR LEARNING 2018
- 14. Future of Workplace Learning: AI Augmentation of existing roles Automation of some roles New roles created Applications in staffing: contract analysis; candidate search © VIR LEARNING 2018
- 15. Future of Workplace Learning: Crypto Public record keeping: democratic, transparent, consistent Evidence of skills & development Applications in staffing: dispute resolution, smart contracts © VIR LEARNING 2018
- 16. Future of Workplace Learning: VR & AR New possibilities for training & learning Immersive, highly customised experience AR training in situ Contextual information © VIR LEARNING 2018
- 17. Future of Workplace Learning: Digitalisation Acceleration through networked infrastructure Efficiencies through smart operations Need to manage processes of change Real-time experimentation Speeding the roll-out of innovation © VIR LEARNING 2018
- 18. Future of Workplace Learning: Analytics Exponential growth in data creation, storage and use Be wary of spurious correlations How can we make sense of the data for learning? Learning is a complex phenomena – can it be reduced to analytics? © VIR LEARNING 2018
- 19. Dealing with digitalisation • What kind of learning content? • How is it being delivered? • How is learning recognised? Orr, Weller & Farrow (2018) © VIR LEARNING 2018
- 20. 21st Century Literacy “The illiterate of the 21st century will not be those who cannot read and write, but those who cannot learn, unlearn, and relearn.” Toffler, A. (1970) Future Shock © VIR LEARNING 2018
- 21. Rethinking learning: e-learning Compliance is important, but can lead to unengaging learning experiences Strong demand for effective learning design Identify longer learning pathways Understand barriers to learning with technology © VIR LEARNING 2018
- 22. Rethinking learning: organisational culture How does your organisation learn? How can you foster creativity and lifelong learning? Integrating development into organisational culture Improve understanding of how your organisation learns and creates knowledge © VIR LEARNING 2018
- 23. The Importance of Vision Technology-enabled People-centric, empowering Supported by learning science Future-facing © VIR LEARNING 2018
Editor's Notes
- VIR established 2018 to offer consultancy to HR and recruitment professionals to help them manage and exploit digital technologies
- James brings a wealth of experience in the recruitment and HR industries. Last year ThinkinCircles won the best Marketing and Pr supplier at the inaugural Recruitment International Supplier awards in London (based on client feedback).
- PhD Philosophy Ed tech research since 2009
- (Talk around how we learn at work) (images need for below) Classroom PC Screen/e-learning/watch and click At desk training What patterns do we see over recent years? (Impact of internet, mobile, etc)
- Why is there a need for VIR? Human capital is important for productivity but also for the fabric of society and social institutions
- We are living through a unique period of accelerated social and technological change Industry 4.0 = World Economic Forum Part of German strategic planning
- We are living through a unique period of accelerated social and technological change. There was once a version of this for smartphones, personal computers, refrigeration, etc.
- Gartner Hype Cycle provides a way to understand the life cycle of technological innovation We are currently at the peak of inflated expectations for a range of technologies e.g. artificial intelligence, machine learning,
- The point is that technological change is disruptive but those ahead of the curve will be in a position to benefit.
- Automation will destroy/create but the risk is not shared equally – occupations with highest estimated automability are lower skilled (and hence, younger). Nb World Bank report Automation will continue to change the workplace Technology as disruptive force: changes in tasks, working patterns, occupational profiles, infrastructure and regulatory frameworks Threat or opportunity? Threat to old ways of doing things but so was refrigeration. New roles emerge based on new technologies, forms of organisation and opportunities for profit Key roles with less vulnerability (recruitment?!) In the future regular learning & development will have enhanced importance The need for soft skills, transferable skills, flexibility, communication skills, etc. in the economy of the future (Nb NOT worsening of working conditions). Does the training offered by people in the room sound like this, or is it characterised by compliance?
- Human capital is important for productivity but also for the fabric of society and social institutions 5 million UK adults lack basic reading, writing and numeracy skills (Joseph Roundtree Foundation, 2016) – technology can widen educational divides What role is technology playing?
- Human capital is important for productivity but also for the fabric of society and social institutions 5 million UK adults lack basic reading, writing and numeracy skills (Joseph Roundtree Foundation, 2016) – technology can widen educational divides What role is technology playing?
- Artificial Intelligence - Breaking the productivity plateau Augmentation of existing operations (e.g. medical diagnosis) Note that the doctor is still needed: augmented, not replaced Applications in HR/development Matching jobs to candidates; Contract analysis AI as misnomer - Can you rely on an algorithim, or do you need human input? Isn’t all AI just augmented intelligence? Nb bias in Amazon recruitment algorithim against women The point is that it just following a script – albeit a complex one. “Predictive Analytics” – recognise a pattern and attempt to follow the rule – is this artificial intelligence? Augmented intelligence? Not general intelligence
- Public record keeping - Effectively promises greater democratization, transparency & consistency Keeping reliable records of training & education Evidence of skills and development Identification and authentication of candidates & their skills Dispute resolution Smart contracts Need for compatibility across systems
- Virtual Reality – creating and experiencing a new kind of digital space Possibilities for training & education through simulation Immersive & branded experiences Augmented Reality Contextual information On the job learning
- rDigitalisation Acceleration through infrastructure Networked systems Worldwide reach Efficiencies through smart operations Rethinking strategies Requires firms to manage process of change Potential to benefit from greater efficiencies Improved real-time measurement of staff activity Real time experimentation Accelerated piloting and rollout of innovation “digital dividend” Digitalisation of people’s lives Privacy/GDPR – again, ethical requirement
- Analytics Exponential growth in data generation, storage and use How to make sense of the data generated with respect to learning Make comparison to learning analytics programme at the OU, MIT – emotional analytics Spurious correlations ”When all you have is a hammer, everything looks like a nail” LEARNING IS A COMPLEX PROBLEM
- Obviously no-one knows what the future will hold, but we can understand the trajectory we are on. The digital ecosystem is evolving rapidly, with disruption bringing both opportunity & risk A simple approach to orientation in this space: OOFAT What kind of content? How is it being delivered? How is learning being recognised? (Orr, Weller & Farrow, 2018) How are we making the most of digital affordances ? Are we planning for change in the best way? Are our staff learning anything? How do we know?
- Artificial Intelligence - Breaking the productivity plateau Augmentation of existing operations (e.g. medical diagnosis) Note that the doctor is still needed: augmented, not replaced Applications in HR/development Matching jobs to candidates; Contract analysis AI as misnomer - Can you rely on an algorithim, or do you need human input? Isn’t all AI just augmented intelligence? Nb bias in Amazon recruitment algorithim against women
- Rethinking elearning Compliance is important, but can lead to learning experiences that don’t engage Effective pedagogy/learning design – move away from paper model Opportunities for peer learning and knowledge exchange Understand barriers to learning with technology Identify longer learning pathways Take advantage of high quality, openly available educational resources
- Avoid technological solutionism - ongoing process of critical reflection Rethinking organisational culture – how does your organisation learn? Ken Robinson – our educational and training systems stifle playfulness and inquiry – all important elements of how we learn but denied since school Foster creativity & independent lifelong learning Integrate development into organisational culture Invest in staff Give staff the skills to review and acquire new knowledge and practices Nurture innovation and capture & amplify effective practice
- 4 principles: A technology-enabled, human-centric economy enabled by the right concepts and forms of engagement