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Great post Sada! I think this delves into the challenge facing many industries right now, where do the humans go when computers take over? It is a scary thought for many displaced workers if even in what is considered the most creative job, advertising, workers are at threat of losing their jobs. One question, though, is what are the inputs AI is using to generate its creative ideas? I imagine that their outputs are still very limited within the box of their inputs, whereas many ad agencies thrive off thinking outside the box (many times with ads that could seem completely unrelated to its industry). I’d also love to know more about the timeline of AI in ad agencies. Do you think this is a threat in the next 50 years or is creative development coming more rapidly?

On November 14, 2018, Bueller? commented on American Express has Struck Gold with Machine Learning :

Thanks PM for the post! My initial reaction was the ethical worries of machine learning using AMEX’s vast sum of data. I would imagine a user being concerned about AMEX looking through his/her purchases, which tend to be privately held. I would be interested to know what precautions AMEX is taking to avoid a Facebook-esque falling out with consumers as it tries to advance it’s big data usage. I think the issue of fraud detection is a very important one as more and more transactions move online making financial data even more important to protect and fraud harder to detect. Does AMEX work with other security companies to help with fraud detection or are the algorithms created from the inside? I’d also be interested to see if machine learning can help in predicting when fraud will happen, making fraud prevention more of proactive and less reactive.

On November 14, 2018, Bueller? commented on Darktrace: Battling Machine Learning Threats, With Machine Learning :

Thanks for the submission Michael Scott! From managing a dying paper industry to analyzing cyber security, you’ve grown a lot with technology! I was surprised to see that 70% of threats come from inside the company. Are most of these from disgruntled workers who, as you would say, have “turntables”? I wonder how effective Darktrace can be from once people on the inside know that their company is using the technology. As you would say, “fool me once, strike one. fool me twice, strike three.” I also wonder if they are working on using this technology for threats from the outside. This seems especially relevant to today’s society as governments and companies across the world are fighting foreign intervention. It’s a scary time. As you would say, “It’s simply beyond words. It’s incalculable.”

On November 14, 2018, Bueller? commented on Discover Weekly: How Spotify is Changing the Way We Consume Music :

Thanks for the post! I was wondering how this has changed, if at all, musicians promotion of their music? Is there a way for them to position themselves in a way to increase the amount of times they are recommended? And how does Spotify currently work with musicians? I know initially there was a lot of hesitations for artists to stream their music. Has that changed now that Spotify is in control of the landscape? How can Spotify continue to work on increasing it’s vast music catalog, which is essential in the success of its music recommendation algorithm. I think your point about level playing field is also very interesting. I think one of the challenges Spotify will face will be recommending songs that are played less frequently. I imagine that right now more popular/known songs are highlighted more often to users and, as a result, this innovation has actually fueled less music exploration.

Thanks for the post Derek! If the NFL Competition Committee decides to release all the teams data, do you think that it will even out the competition across the league? It seems like machine learning in play calling has the potential to diminish the effects of skilled players and coaches. I wonder if you have any thoughts about how teams differentiate themselves in a future of automated play-calling. I’m also curious as to how college teams have embraced machine learning and the lag they have relative to the NFL. And lastly, I think the potential for machine learning in play-calling to make the sport safer is very interesting. I think the league has a real opportunity to analyze which plays lead to higher amounts of injuries/concussions that could potentially mitigate the recent negative press the NFL has received around safety issues.

On November 14, 2018, Bueller? commented on San José Tackles Open Innovation for Smart Cities :

Thanks for your post Nancy, this is awesome! I agree having a Chief Innovation Officer and open innovation in city governments is incredibly important to the future services a city can provide. I was wondering though how San Jose has prioritized certain issues as it decides what to tackle first? With a limited budget and resources, I imagine prioritization is extremely important in getting things done. I also was wondering what lessons from San Jose you think can be taken to cities across the country? If San Jose does succeed in becoming the most innovative city in the country, it’s important that we spread its success story in an effective way so that other local governments can tackle similar issues, even without the benefit of a larger government and the close proximity to the tech center of the world. And my last question is how has San Jose local government worked alongside state government? I wonder if a partnership across innovation teams could help bring its innovation to scale and ensure a longer-term outlook.