I do not believe that civic duty is enough to incentivize the most innovative citizens to invest their time and energy in improving their cities future, when a more lucrative and stable career is waiting for them at the doorstep of any large company. This is the biggest issue with government these days: we are not investing enough money in getting the best talent our country has to offer to work on solving our communities’ problems. We underpay civil servants, we do not recruit on campuses, and we do not take care of those few people who dedicate their lives to public service. If we want open innovation to really work, we need to put our money where our mouth is.
This is a very interesting essay Ian. Great job! The only concern I had when reading about this initiative is how do we regulate the types of projects that people invest in? How do we make sure that those projects are doing good for the community in the long run, and are not simply a pet project that a rich investor cares about? I think that this platform is very interesting, but there is an inherent tension between democratizing project investments and pushing through projects that may not be popular to capital holders but may provide tremendous value for local communities.
Thanks for sharing Carlos! I wonder how regulators will react to this type of manufacturing replacing traditional manufacturing for companies like GE. It could have wide-reaching societal impact and I personally that companies like GE will have to think about the societal implications before taking these processes mainstream. But that brings up an important question: are companies responsible for subsidizing employees who are not adding as much value as machines? Or are they accountable to their shareholders to reduce costs in whatever way they can?
This is a very interesting article! Though I do think that 3d printed food could have some very good practical uses, I wonder how difficult it would be for such a product to be diffused in the mainstream. We have been eating food the same way for centuries, and I feel like many people will find it strange for their food to be built molecule by molecule by a machine. I wonder how the manufacturers/marketers of this product are thinking about surmounting this challenge.
Thanks for the interesting read! I really appreciate the research you put into this. I find it really interesting how self-driving trucks are already being piloted while self-driving cars are still struggling to gain regulatory approval. I think this probably has a lot to do with how self-driving trucks operate in a much more controlled environment. I wonder whether some of the lessons that engineers learn from deploying self-driving trucks to roads will help speed up the research and development of market-ready self-driving cars.
Thanks for the interesting read! I think that this countering human bias is one of the biggest challenges with regards to machine learning. I would argue that the reason that these biases occur is because machine learning algorithms do not discriminate between correlated relationships and causal relationships. We should strive to collect enough data on our processes to reveal true causal relationships which provide more accurate predictions than using correlated data. If we can improve data collection in this way, we can counter those biases.