Edtech summit 2018 - Unlearning to learn
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The document discusses how artificial intelligence is being applied in various fields and jobs. It describes several AI systems that have been developed for tasks such as creating news articles, generating realistic images, assisting doctors in diagnosis, playing strategic games, and serving as personal assistants. It also discusses how AI may eventually match and even surpass human levels of intelligence and ability. The skills needed in the future will center around complex problem solving, critical thinking, and managing people as AI automates more routine tasks. The impact and possibilities of AI are vast but also uncertain.
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Edtech summit 2018 - Unlearning to learn
- 1. Unlearning to Learn Fostering Intrinsic Learning Motivation in the Modern Workplace https://unsplash.com/photos/OsC8HauR0e0
- 2. Introduction My journey to what I do today, I believe has a strong connection with what I have been exposed to, especially in my earlier childhood. I grew up in a town about 2 hours drive from the capital - Jakarta. During those days, I spent my time mainly playing different characters.
- 3. I grew up watching futuristic TV series and movies: - Buck Rogers, Battlestar Galactica, Startrek, Starwars, Bionic woman, Knight Riders, - and a healthy dose of Japanese anime (and still today) I dreamt going on an adventure to explore the space, to find never seen before things and places, conquer adversities and emerge triumphant The exposure of such stories has greatly influenced the
- 4. Meet Aye! I believe we are at a crucial junction where the rapid pace of technology developments are affecting and impacting the way we live now and with some ramifications for the near future -- for better or meh. Every day, we are producing bits of data, consciously or unconsciously through our actions. These data are collected, analysed and lead to more ideas that aim to help us to become
- 5. In 2016, The Washington Post launched Heliograf, at the Rio Olympics. Heliograf is an IA system that helped WAPO Olympic coverage by automatically create articles covering up-to-date event coverage, match Reporter
- 6. NVIDIA is a technology hardware company, recently created another AI system that is used to create a fake human character that is uber realistic and believable. Hard to discern by normal human’s eye. The project is part of a vast and varied effort to build technology that can automatically generate convincing images — or alter existing images in equally convincing ways. They hope to accelerate and improve the creation of media, eventually allowing software to create realistic imagery in moments rather than the hours — if not days https://www.nytimes.com/interactive/2018/01/02/technology/ai-generated-photos.html Digital actress
- 7. NVIDIA is a technology hardware company, recently created another AI system that is used to create a fake human character that is uber realistic and believable. Hard to discern by normal human’s eye. The project is part of a vast and varied effort to build technology that can automatically generate convincing images — or alter existing images in equally convincing ways. They hope to accelerate and improve the creation of media, eventually allowing software to create realistic imagery in moments rather than the hours — if not days https://twitter.com/johnkrafcik/status/1020343952266973186 Driver / chauffeur
- 8. In 2017 the American Academy of Ophthalmology published a report detailing the progress of the AI system in helping ophthalmologist identify ocular diseases. The report suggests that the AI system has consistently identified ocular diseases at a rate that surpasses human diagnosis. Doctor assistant https://www.aao.org/eyenet/article/artificial-intelligence
- 9. In 2016, the alphaGo system developed by Google DeepMind team beat the reigning world champion Lee Sedol in a decisive 4-1 victory. Mastering the game - Go - has been seen as the holy grail of AI development. This is significantly different from the game of chess where logic is the primary determining factor to win. To win a Go game, world’s mathematicians could only approximate that there about 10 to the power 700 possible move. This showed that a machine has approximated human- level intelligent. The machine that actually learns on their own. AlphaGo team went on to develop AlphaGo Zero which won convincingly against the original AlphaGo 100-0 -- Zero managed to reach a Master level in 21 days compared to the older version that took 40 days Strategy game player (champion)
- 10. This year in May at Google yearly event, Google CEO - Sundar Pichai - demoed Google Assistant for the first time. The demo showed that an AI-powered virtual assistant was able to schedule a haircut for its owner, by calling a hair saloon and conversing as how a normal human would. This showed that now technology can understand the context that surrounds human conversations and made the necessary responses to get to the outcome required. https://www.youtube.com/watch?v=ogfYd705cRs Personal assistant
- 11. How far will it go? What will we do with the extra time?
- 12. Max Tegmark of MIT shared an appropriate abstract landscape of tasks, where the elevation represents how hard it is for AI to do each task at human level, and the sea level represents what AI can do today. The sea level is rising as AI improves, so there's a kind of global warming going on here in the task landscape.
- 13. And the obvious takeaway is to avoid careers at the waterfront -- which will soon be automated and disrupted. But there's a much bigger question as well. How high will the water end up rising? Will it eventually rise to flood everything, matching human intelligence at all tasks AGI (Artificial General Intelligence)
- 14. The world economic forum did a research in 2016/17 involving approximately 13.5 millions employees globally across different industries. They identified that the top 10 foundational skills in 2020 will centred around complex problem solving, critical thinking, creativity, people management -- all the way to cognitive flexibility. Top 10 skills http://reports.weforum.org/future-of-jobs-2016/
- 16. “... as we know, there are known knowns; there are things we know we know. We also know there are known unknowns; that is to say we know there are some things we do not know. But there are also unknown unknowns - the ones we don't know we don't know.” Donald Rumsfeld former U.S. Defense Secretary
- 17. expertise tend to be the most conservative people in the organisation. Complex Probe > sense > respond This is the area where the cause and effect relationship is so intertwined and things only make sense in hindsight. When something happens, everyone quick to rationalise the reason why thing happens is because of x y z. If you have the ability to record the entire process leading to the final effect, every time you rewind and play the video, you would end up getting a different result. The reason for this, the complex space is about the network that connected to each other. The relationships are non linear, a small activity in one part of the network could have an impact somewhere else, and vice versa. Things are unpredictable in detail and the way you make progress is to sense the patterns that are in there. Things are never complete like culture, innovation, leadership, people relationship and all the messy people things. Chaos Act > sense > respond complicated simple complex chaos
- 18. complicated simple complex chaos culture, innovation, leadership, people relationship and all the messy people things. Are we spending enough time to really understand ourselves?
- 19. “The illiterates of the 21st century will not be those who cannot read and write but those who cannot learn, unlearn, and relearn.” Alvin Toffler American writer, futurist, and businessman
Editor's Notes
- I grew up watching futuristic TV series and movies: - Buck Rogers, Battlestar Galactica, Startrek, Starwars, Bionic woman, Knight Riders, - and a healthy dose of Japanese anime (and still today) I dreamt going on an adventure to explore the space, to find never seen before things and places, conquer adversities and emerge triumphant The exposure of such stories has greatly influenced the work that i do today, and more so because some are becoming a reality.
- In 2016, The Washington Post launched Heliograf, at the Rio Olympics. Heliograf is an IA system that helped WAPO Olympic coverage by automatically create articles covering up-to-date event coverage, match fixture and event results. The technology was successful, and WaPo continues to further develop it and use it to publish hundreds of articles last year.
- NVIDIA is a technology hardware company, recently created another AI system that is used to create a fake human character that is uber realistic and believable. Hard to discern by normal human’s eye. The project is part of a vast and varied effort to build technology that can automatically generate convincing images — or alter existing images in equally convincing ways. They hope to accelerate and improve the creation of media, eventually allowing software to create realistic imagery in moments rather than the hours — if not days
- WAYMO (part of Google) recently has completed eight million miles of test drive on public roads with no accidents (to my knowledge) - thanks to their early riders programme And they are on their way to offer the service to the public soon. Elon Musk, in one of his interviews, said, “by 2018, the autonomous vehicles will be able to drive safer than any safest human drivers.” I think his prediction may be correct
- In 2017 the American Academy of Ophthalmology published a report detailing the progress of the AI system in helping ophthalmologist identify ocular diseases. The report suggests that the AI system has consistently identified ocular diseases at a rate that surpasses human diagnosis.
- In 2016, the alphaGo system developed by Google DeepMind team beat the reigning world champion Lee Sedol in a decisive 4-1 victory. Mastering the game - Go - has been seen as the holy grail of AI development. This is significantly different from the game of chess where logic is the primary determining factor to win. To win a Go game, world’s mathematicians could only approximate that there about 10 to the power 700 possible move. This showed that a machine has approximated human-level intelligent. The machine that actually learns on their own. AlphaGo team went on to develop AlphaGo Zero which won convincingly against the original AlphaGo 100-0 -- Zero managed to reach a Master level in 21 days compared to the older version that took 40 days
- This year in May at Google yearly event, Google CEO - Sundar Pichai - demoed Google Assistant for the first time. The demo showed that an AI-powered virtual assistant was able to schedule a haircut for its owner, by calling a hair saloon and conversing as how a normal human would. This showed that now technology can understand the context that surrounds human conversations and made the necessary responses to get to the outcome required.
- All this advancement in AI begs the question: How far will it go?
- Max Tegmark of MIT shared an appropriate abstract landscape of tasks, where the elevation represents how hard it is for AI to do each task at human level, and the sea level represents what AI can do today. The sea level is rising as AI improves, so there's a kind of global warming going on here in the task landscape.
- And the obvious takeaway is to avoid careers at the waterfront -- which will soon be automated and disrupted. But there's a much bigger question as well. How high will the water end up rising? Will it eventually rise to flood everything, matching human intelligence at all tasks
- The world economic forum did a research in 2016/17 involving approximately 13.5 millions employees globally across different industries. They identified that the top 10 foundational skills in 2020 will centred around complex problem solving, critical thinking, creativity, people management -- all the way to cognitive flexibility.
- Worth noting, cognitive flexibility is new and was not listed in the past report. Cognitive flexibility is the human ability to adapt the our thinking & learning strategies to face new and unexpected conditions in the environment. Worth noting, the list also suggests a strong theme around cross-functional skills. We are expected to work well in a team setting. To execute missions relevant for the success of the organisations that we work for. In my opinion there’s still another layer which often overlook - the critical part where in the absence of it will make cross collaborating impossible.
- The former Secretary of Defence Donald Rumsfeld eloquently said “Reports that say that something hasn't happened are always interesting to me, because as we know, there are known knowns; there are things we know we know. We also know there are known unknowns; that is to say we know there are some things we do not know. But there are also unknown unknowns- the ones we don't know we don't know.” - Known question known answers - Known question unknown answers - Unknown question known answers - Unknown question unknown answers
- Dave Snowden, introduced Cynefin in 1999 while at IBM. Cynefin pronounced as kuh-nev-in, a Welsh word that literally mean habitat / environment. Is made up 4 domains to represent how and why things happen in organisation and life. I want to make a distinction here that everything that happens in organisation also happen outside of work Simple Sense > categorize > respond Simple domain is where cause = effect relationship is very well known If you do x you always get X. No matter how many times you do X you will always get Y. You always get the same answer. Things work in this domain is like - Standard operating procedure - best practices You will end up knowing that you will have one or few good answers Complicated Sense > analyze > respond The next domain is the complicated domain. There’s a relationship between x & y. Effort is required to understand the relationship between the 2 variables. You need to analyse the relationship, and work out what are the possibilities. You need to have the expertise to analyse the cause and effect that leads to solutions. You engage the experts or build the capability to have the expertise. People who put in the effort in developing the expertise tend to be the most conservative people in the organisation. Complex Probe > sense > respond This is the area where the cause and effect relationship is so intertwined and things only make sense in hindsight. When something happens, everyone quick to rationalise the reason why thing happens is because of x y z. If you have the ability to record the entire process leading to the final effect, every time you rewind and play the video, you would end up getting a different result. The reason for this, the complex space is about the network that connected to each other. The relationships are non linear, a small activity in one part of the network could have an impact somewhere else, and vice versa. Things are unpredictable in detail and the way you make progress is to sense the patterns that are in there. Things are never complete like culture, innovation, leadership, people relationship and all the messy people things. Chaos Act > sense > respond There is no perceivable relationship between cause and effect. You simply need to take action, there’s no rule since it’s chaotic. Don’t over plan, overthink - just act on it. The result will push you into one of the 3 domains where you can start
- culture, innovation, leadership, people relationship and all the messy people things.
- We need to acknowledge that we have always been operating in complex domain. So what is necessary to have a growth mindset? open-mindedness?