Great article and highly relevant in today’s context. Thanks for sharing a perspective on the darker side of crowdsourcing and open-innovation. To address your question, I believe that it is critical for users of any type of popular social media technologies to be educated about their privacy risks. Education is truly the first line of defence. This type of education can come in many forms – formal training by the government/company, or self-guided training through online videos that teach users the type of data social media companies collect (e.g., location data, timestamp data, other personal data).
Fantastic article – and thanks for highlighting this type of open-innovation in the context of Toronto (I love Canada!).
Like you, I believe that Sidewalk Lab’s approach to creating smart cities is a great idea. It follows a similar model to “The Lean Startup”, which highlights how most successful startups adopt this mindset of speaking to customers constantly and iterating on the product immediately to solve problems for customers. However, at some point, there needs to be a visionary leader who uses judgement to pick out which of the “crowd-sourced” ideas is truly worthwhile in terms of impact – that decision cannot (and should not) be crowd-sourced.
Thanks for writing such an insightful and well-structured analysis of additive manufacturing in the context of GE. With GE’s new CEO, my hope is that they will sell off parts of the business that are a distraction to GE’s future growth in engineering and manufacturing. This way, GE can focus on maintaining a positive cash flow so that they can then acquire emerging companies that have additive manufacturing capabilities instead of building those capabilities in-house.
Interesting article about 3D printing and how it applies to the broader political climate (i.e., gun control in the US). I’m with a similar opinion as expressed in previous comments – this technology for 3D printing guns is absolutely terrifying. There’s no clear way for anyone to regulate such a technology and the “pay what you want” model makes this gun easily accessible to anyone with internet access. As 3D printing becomes more pervasive and affordable (e.g. a functioning 3D printer can be purchased at Walmart for $169 USD), there is an increased likelihood that people with malicious intent (and whom normally would not pass a background/safety check) can easily make their own guns at home to cause harm.
This technology needs to be made illegal with severe consequences attached to offenders.
Thanks for such a thought-provoking article. I particularly enjoyed how you are bringing up opportunities that bridge the knowledge gap between the public and private sectors. When it comes to investing in and adopting new technologies like machine learning, government organizations (e.g., the British Army) should create a separate division that is able to experiment and test in a slow and controlled environment. This way, the process aligns with the government’s pace of adopting new ideas, and at the same time collect enough data points to improve on the machine learning applications before broadly implementing to other system-wide departments.
Interesting article. I like how well-structured your argument is for how machine learning can be used to improve both the design and manufacturing process of Airbus planes. The biggest concern I see about applying Airbus’s machine learning capabilities to “self-driving planes” is the lack of overlap there is into the two different types of use cases. In the current case, machine learning is being applied to tackle incremental changes to manufacturing and making plane production more efficient. “Self-driving planes”, on the other hand, require a more transformative and breakthrough technological advancement. This new application would directly impact the amount of talent and resources Airbus would need to make self-driving planes come true.