Thanks for sharing! This article made me consider which types of companies open innovation is useful for and for whom it might be a false signal. Like we saw with LEGO, perhaps crowd-sourcing from power users actually causes them to develop products for the wrong target audience. I also wonder whether more broadly it makes sense for a company to use open innovation if they are losing buyers, since they will likely just appease the people who already love their products versus understanding why people aren’t using LEGOs. It reminds me of IDEO interviewing ‘extreme’ users — it’s important to understand both why people love your product as well as why people don’t use your product. Perhaps it could be a useful tool for idea generation but they’d just want to make sure they balance that with other methods of understanding user behavior and requests.
Great question. The data comes from a few sources — for things like weather predictions it comes from public databases like weather.gov. Some data is crowd-sourced, so it comes from other farmers’ data that has either been uploaded manually by users of Climate FieldView or uploaded automatically via sensors, drones, and other technology the farmer might be using. Everything runs off of the cloud so it’s all iterative and learns as it ingests or receives more data. So, to your point it is iterative and there are network effects. For example if a farmer uploads a picture of a crop because he’s wondering what disease it has, that is compared to pictures of the same crops that other farmers have uploaded.
Great read and a fascinating topic. While I love the idea of getting more people involved in legislation and government, I am actually really concerned about problems with equal access and abuse. I echo Joe’s concerns about governments or lobbyists buying “votes” and manipulating the outcome, while being able to claim the process as “democratic” and thus legitimizing their own ideas without giving the public power to hold them accountable. Further, to your point about making it easier for more people to participate, I think that ease of use would also be important to ensure everyone’s voices are heard equally. While it could potentially make it easier for marginalized voices to participate in this type of system (especially given some of the voter registration issues we have in the U.S.), one concern I have is whether this is driving the ‘digital divide’ even wider. There is already so much separation between the “digital haves” and “have nots”, I worry that this could perpetuate the issue and further drown out marginalized voices.
Interesting topic. I can see a lot of applications for this, but the military comes to mind since the cost of transporting healthy food is so expensive — especially for anything refrigerated or not dense (e.g. carrying vegetables isn’t possible). To your point on sustainability and making new types of foods appetizing, I could also see this 3D printer being useful once we reach the point where we can make lab-grown meat. There is actually a company in Israel who is experimenting with this: https://www.livekindly.co/hummus-company-lab-grown-steak/. They grow the meat in a lab and then use 3D printing to give it the right texture. While I think we are still a long way off from lab grown meat being socially accepted, this could help.
It seems like the company is mostly focused on higher-end markets (e.g. people who want to print their dinner on the way home), but I like your applications of using it for the elderly and sustainability. Are they focused on this in the short-term or long-term?
Great example of how additive manufacturing can provide positive societal benefits, but I love the ethical and regulatory questions you posed. To your question about the difference between whether there will be significant differences in who can afford this in the future, do you think this is significantly different than the disparities in health care access today? I could see a world where this makes healthcare more affordable, since speeding up the time and reducing cost of clinical trials could make things like cancer treatment more affordable. I am also curious whether this could help with organ rejection. I could potentially see a world where you grow organs with the person receiving the transplant’s gene, and having this help with rejection.
This is a really interesting company, I can see a lot of applications for this across sectors. For exampe, consolidating market research reports or helping policy makers and academics read through large quantities of academic reports. Regarding your question about journalism, one of the things I really value in journalism is the point of view and analysis that a journalist provides. In addition, a big part of journalism is interviewing people to draw out insights and develop narratives and stories. While I can see this being useful for summarizing facts, I think a human can provide unique insights and storytelling aspects to make stories truly come to life and provide analysis and a point of view. To me, this seems like a great example of how machine learning can augment a person’s job and give them more room for creativity.
This is a fascinating application of machine learning. I think this is important for two reasons. 1) There is so much stigma attached to asking for help that this is a way for someone to get help when they are incapable of asking for it themselves. 2) Considering how many objective and diagnostic tests we have for other illnesses while mental health is typically diagnosed through self-reported or more subjective diagnostic tools, I could see this being a useful tool for a more objective type of diagnosis. It could be a great way to sense the beginning of a crisis and respond accordingly, and I could even see this connected to crisis hotlines or peer support groups. I do worry about data privacy concerns. Do we think there are any downsides to this? On the one hand, it’s incredibly important. On the other hand, if this data gets hacked or stolen I could see massive and horrifying openings for abuse.