Muneeb Ahmed's Profile
Thank you for writing this, Shuyao!
I wonder, though, is cryptocurrenfy necessary for this system of bounties? Or, rather, can we accomplish the same thing by using digital USD? As an ordinary citizen who wants to do good for money, I am sometimes a little concerned about receiving payment in cryptocurrency. And since cryptocurrencies require resources to mine and accumulate, why not just use regular USD?
Thanks for addressing this topic.
I am a little concerned about the adverse impact that “safety” equipment can have. For example, with the use of gloves in boxing, the number of fatalities has sharply increased. Before, a human’s knuckle or wrist would break with enough impact upon a human skull. However, with the cushion of a glove, the risk to the head has increased significantly. My concern is that with ostensibly “safer” helmets, the NFL may make certain illegal helmet-to-helmet hits legal again because helmets can handle more impact. But because of this “safer” helmet, players may be more willing to take risks with their bodies and end up causing themselves even more harm.
Hey Dan, thanks for writing this!
I am concerned about the diffusion of blueprints for 3D-printed to non-military actors. If, say, a grenade launcher can be easily printed with the right blueprints and, assuming that grenades are easier to come by than grenade launchers, wouldn’t this make the possibility of non-state actors acquiring very lethal machinery much easily? What steps is the military taking to safeguard this knowledge and prevent its proliferation? If it is inevitable that non-state actors will be able to acquire the information (perhaps from rogue states), what can the military do in response to non-state actors who have easy access to advanced weaponry via 3D printing?
Thanks for writing this, Trey! I learned a lot.
My question after reading this is whether machine learning can do more than forecast when maintenance is needed. Can it, for example, toggle between renewable and non-renewable sources when the former are much more abundant because of favorable conditions (better wind conditions, higher levels of sunlight)? Perhaps my question is quite naive and electricity grids don’t actually work that way, but I am wondering if AI will take us into a world where it does more than flag things for maintenance but rather take action before humans can.
Hi! I am sorry. It appears my footnotes disappeared when I added my word count. Here they are!
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2. Arthur Herman, “China’s Brave New World of AI,” Forbes, August 30, 2018, [https://www.forbes.com/sites/arthurherman/2018/08/30/chinas-brave-new-world-of-ai/#18fae4c728e9], accessed November 2018.
3. Hassan Chowdhury, “China’s Tech Spending More on AI Than Silicon Valley,” The Daily Telegraph Technology Intelligence, October 7, 2018, [https://www.telegraph.co.uk/technology/2018/10/07/chinas-tech-giants-spending-ai-silicon-valley], accessed November 2018.
4. Christina Larson, “China’s Massive Investment in AI Has an Insidious Downside,” Science Mag, February 8, 2018, [https://www.sciencemag.org/news/2018/02/china-s-massive-investment-artificial-intelligence-has-insidious-downside], accessed November 2018.
5. Paul Mozur, “Inside China’s Dystopian Dreams: A.I., Shame and Lots of Cameras,” The New York Times July 8, 2018, [https://www.nytimes.com/2018/07/08/business/china-surveillance-technology.html], accessed November 2018.
6. Yuan Yang, “China Seeks Glimpse of Citizens’ Future with Crime-Predicting AI,” The Financial Times July 23, 2017, [https://www.ft.com/content/5ec7093c-6e06-11e7-b9c7-15af748b60d0], accessed November 2018.
7. Tara Francis Chan, “Debtors in China Are Placed on a Blacklist That Prohibits Them from Flying, Buying Train Tickets, and Staying at Luxury Hotels,” Business Insider December 19, 2017, [https://www.businessinsider.com/chinas-tax-blacklist-shames-debtors-2017-12], accessed November 2018.
8. “China to Bar People with Bad ‘Social Credit’ from Planes, Trains,” Reuters March 16, 2018, [https://www.reuters.com/article/us-china-credit/china-to-bar-people-with-bad-social-credit-from-planes-trains-idUSKCN1GS10S], accessed November 2018.
9. Christopher Udemans, “Blacklists and redlists: How China’s Social Credit System actually works,” Business Insider October 23, 2018, [https://technode.com/2018/10/23/china-social-credit/], accessed November 2018.
10. “Detentions of Uighurs Must End, UN Tells China Amid Claims of Mass Prison Camps,” The Guardian August 30, 2018, [https://www.theguardian.com/world/2018/aug/31/detention-of-uighurs-must-end-un-tells-china-amid-claims-of-mass-prison-camps], accessed November 2018
11. Lopez-Iturriaga, Felix Javier and Pastor-Sanz, Iván, Predicting Public Corruption with Neural Networks: An Analysis of Spanish Provinces (November 22, 2017). Social Indicators Research, Forthcoming . Available at SSRN: https://ssrn.com/abstract=3075828 or http://dx.doi.org/10.2139/ssrn.3075828
12. “Benefits and Risks Involved in AI-Powered Fraud Detection,” CIO Review September 12, 2018, [https://www.cioreview.com/news/benefits-and-risk-involved-in-aipowered-fraud-detection-nid-27120-cid-175.html], accessed November 2018
Great write-up, Casilda!
I wanted to ask – is there still a significant human element in all of this? Meaning, is the labeling portion heavily dependent on humans? I am hoping that maybe, eventually, we can move to a world where machine learning is detecting new types of fraud that humans would have never noticed in the first place. Additionally, I worried if we’re relying on humans to detect and label fraud, we’ll always be one step behind the fraudsters themselves.