6.1 Collective Intelligence, and Too Many Links
I ended up deciding to make Week 6 and 7 two-part blogs because even though the Sessions notes didn't require them, the brief kind of did? I've actually already exceeded 3000 words if you include the text in the concept posts, but it's a min not a max so good luck with the reading, Julian :D)
From Aristotle's early musings on automation, to Asimov's "Runaround", robots have inspired fear as well as awe in humans. Our relationship with the idea of robots has been reflected in their portrayal in media. We've dreamt up Jetson's-style worlds in which they can enrich our lives, as well as dystopian futures where robots have supplanted humans and use us as batteries. For now, we're still amused as early robots stumble over themselves, or annoyed as Alexa mis-hears what command you're telling her. But their progress is already much faster than we had anticipated, and we are facing the possibility of a world where robots will be a part of many facets of our lives.
In terms of industrial robot adoption, Asian countries seems to be ahead of the curve, compared to its European and American counterparts. According to the International Federation of Robotics (IFR), Korea and Singapore currently take the lead, with 710 and 658 robots per 10,000 workers respectively (Winick, 2018). Whether increased industrial robot adoption is something to be encouraged depends on where you stand when it comes to job security. On one hand, robots help greatly when it comes to jobs that are dangerous or mindlessly repetitive. However, the question on how unskilled workers will be able to cope with increased job losses in the future is still an unanswered one.
Machine learning, which may or may not have physical components. "is a branch of artificial intelligence" that is "the study of computer algorithms that improve automatically through experience" (Mitchell, 2018) The term is often used as equivalent to Artificial Intelligence, even though it's not. AI instead “is aspirational, a moving target based on those capabilities that humans possess but which machines do not.” (Lipton, 2018). Andrew Moore, the new head of Google's Cloud AI business, expressed frustration at the common perception that AI is somehow a kind of "Magic dust" that can improve an organization, rather than the reality which is that AI implementation can take a lot of work.
The current state of machine learning is also not without its issues. There's very little research when it comes to making sure facial recognition technology built using machine learning isn't biased. This becomes a problem when facial recognition is used by police forces to profile and identify people of different racial groups. Joy Buolamwini refers to this as the "coded gaze", where AI systems become shaped by "the priorities and prejudices - conscious and unconscious - of the people who design them" (Buolamwini, 2018). It matters to pay attention to who is coding (is the team diverse?), how they code (is there sufficiently represented data?), and why they code (do they approach the task with inherent bias that might end up in the code?).
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| Serve, a robot that will deliver groceries and lunch in LA (Firth, 2018) |
Video of Robotic Cowboy that waves trash bags around to keep people from being trampled by cows (Winick, 2018)
Machine learning, which may or may not have physical components. "is a branch of artificial intelligence" that is "the study of computer algorithms that improve automatically through experience" (Mitchell, 2018) The term is often used as equivalent to Artificial Intelligence, even though it's not. AI instead “is aspirational, a moving target based on those capabilities that humans possess but which machines do not.” (Lipton, 2018). Andrew Moore, the new head of Google's Cloud AI business, expressed frustration at the common perception that AI is somehow a kind of "Magic dust" that can improve an organization, rather than the reality which is that AI implementation can take a lot of work.
The current state of machine learning is also not without its issues. There's very little research when it comes to making sure facial recognition technology built using machine learning isn't biased. This becomes a problem when facial recognition is used by police forces to profile and identify people of different racial groups. Joy Buolamwini refers to this as the "coded gaze", where AI systems become shaped by "the priorities and prejudices - conscious and unconscious - of the people who design them" (Buolamwini, 2018). It matters to pay attention to who is coding (is the team diverse?), how they code (is there sufficiently represented data?), and why they code (do they approach the task with inherent bias that might end up in the code?).
In conclusion, after going through nearly 50 links that include videos, and links to more links (thanks Julian), I can definitely see how the future of the creative industry is also going to inevitably intersect with AI and machine learning in many ways. I was particularly intrigued by the idea that virtual robots teaching themselves kung fu would change the way we design games and animated films (maybe even paving the way for humans to learn martial arts by downloading it into our minds?) Issues related to ownership and ethics are already being discussed, but it needs to be in the forefront of our minds as we progress, rather than figuring things out after the technology has been in use.
Bibliography:
Buolamwini, J. (2018). When the Robot Doesn't See Dark Skin [online] The New York Times. Available at: https://www.nytimes.com/2018/06/21/opinion/facial-analysis-technology-bias.html [Accessed 23 Dec. 2018]
Buolamwini, J. (2018). When the Robot Doesn't See Dark Skin [online] The New York Times. Available at: https://www.nytimes.com/2018/06/21/opinion/facial-analysis-technology-bias.html [Accessed 23 Dec. 2018]
Firth, N. (2018). Postmates has launched a delivery robot that will bring lunch to your door [online] Technology Review. Available at: https://www.technologyreview.com/the-download/612605/postmates-has-launched-a-delivery-robot-that-will-bring-lunch-to-your-door/ [Accessed 23 Dec. 2018]
Hao, K. (2018). Establishing an AI code of ethics will be harder than people think [online] Technology Review. Available at: https://www.technologyreview.com/s/612318/establishing-an-ai-code-of-ethics-will-be-harder-than-people-think/ [Accessed 23 Dec. 2018]
Iriondo, R. (2018). Differences Between AI and Machine Learning and Why it Matters [online] Medium. Available at: https://medium.com/datadriveninvestor/differences-between-ai-and-machine-learning-and-why-it-matters-1255b182fc6 [Accessed 23 Dec 2018]
Knight, W. (2018). AI is not "magic dust" for your company, says Google's Cloud AI boss [online] Technology Review. Available at: https://www.technologyreview.com/s/612394/ai-is-not-magic-dust-for-your-company-says-googles-cloud-ai-boss/?set= [Accessed 23 Dec 2018]
Knight, W. (2018). Virtual robots that each themselves kung fu could revolutionise video games [online] Technology Review. Available at: https://www.technologyreview.com/s/610773/virtual-robots-that-teach-themselves-kung-fu-could-revolutionize-video-games/ [Accessed 23 Dec. 2018]
Hao, K. (2018). Establishing an AI code of ethics will be harder than people think [online] Technology Review. Available at: https://www.technologyreview.com/s/612318/establishing-an-ai-code-of-ethics-will-be-harder-than-people-think/ [Accessed 23 Dec. 2018]
Iriondo, R. (2018). Differences Between AI and Machine Learning and Why it Matters [online] Medium. Available at: https://medium.com/datadriveninvestor/differences-between-ai-and-machine-learning-and-why-it-matters-1255b182fc6 [Accessed 23 Dec 2018]
Knight, W. (2018). AI is not "magic dust" for your company, says Google's Cloud AI boss [online] Technology Review. Available at: https://www.technologyreview.com/s/612394/ai-is-not-magic-dust-for-your-company-says-googles-cloud-ai-boss/?set= [Accessed 23 Dec 2018]
Knight, W. (2018). Virtual robots that each themselves kung fu could revolutionise video games [online] Technology Review. Available at: https://www.technologyreview.com/s/610773/virtual-robots-that-teach-themselves-kung-fu-could-revolutionize-video-games/ [Accessed 23 Dec. 2018]
Reach Robotics (2018). 18 Defining Moments In The History of Robotics [online] Medium. Available at: https://medium.com/@ReachRobotics/18-defining-moments-in-the-history-of-robotics-761de7a2fbba [Accessed 23 Dec. 2018]
Simon, M. (2018). The Wired Guide to Robots [online] Wired. Available at: https://www.wired.com/story/wired-guide-to-robots/ [Accessed 23 Dec. 2018]
Winick, E. (2018). These charts show how Asia is dominating industrial-robot adoption. [online] Technology Review. Available at: https://www.technologyreview.com/s/612475/these-charts-show-how-asia-is-dominating-industrial-robot-adoption/ [Accessed 23 Dec 2018]
Winick, E. (2018). This robotic cowboy is waving trash bags to keep people from being kicked by cows [online] Technology Review. Available at: https://www.technologyreview.com/the-download/612382/this-robotic-cowboy-is-waving-trash-bags-to-keep-people-from-being-kicked-by/ [Accessed 23 Dec. 2018]
Winick, E. (2018). These charts show how Asia is dominating industrial-robot adoption. [online] Technology Review. Available at: https://www.technologyreview.com/s/612475/these-charts-show-how-asia-is-dominating-industrial-robot-adoption/ [Accessed 23 Dec 2018]
Winick, E. (2018). This robotic cowboy is waving trash bags to keep people from being kicked by cows [online] Technology Review. Available at: https://www.technologyreview.com/the-download/612382/this-robotic-cowboy-is-waving-trash-bags-to-keep-people-from-being-kicked-by/ [Accessed 23 Dec. 2018]
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