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Frasier
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The massive potential of AM in the aerospace industry is not something that I had considered before, but clearly, as explained above, has significant potential. Not only could it keep aircraft in operation at lower cost over longer periods of time (once spare parts replacement manufacturers have stopped producing those parts), but it also has the ability to keep aviators flying by giving them the tools they need to produce replace parts while in the field. While determining how AM could reduce variability in its printed products to meet the standards fo the FAA is certainly a challenge, the value of the potential benefits indicate to me that there will be plenty of people in the defense industry working to overcome these challenges, even for critical parts. In other words, with appropriate technology development–for which I believe there is immediacy to develop–I believe the FAA will, eventually, approve the use of AM to produce replacement parts.
The use of open innovation to combat cyberterrorism against the U.S. government is a fascinating application of the method at a federal scale. Particularly where there is a ready and able community of hackers, who might love the prestige of hacking into government security systems, this is an innovative way of leveraging those motivations in a positive way for the government. The security implications deserve their own consideration, and could not possibly be dealt with in a comprehensive manner here, but I will add another aspect to question is: is welcoming people to hack the U.S. government in a constructive way encourage them to hack the U.S. government in a destructive way?
In a world where NASA’s funding is under threat of being cut, using open innovation to help generate ideas and solutions, while only paying on a success basis, is a highly strategic way to continue to operate at a high level while keeping operating costs low. However, I agree that there is reason for concern in thinking about how this move will affect long-term strategic planning.
Open Innovation in this context would be most helpful for discrete challenges, particularly ones where there is little threat of competition. However, investing in something like the mission to send a man to the moon, which was a ten-year project, would require tight project management and direction from within NASA itself. The company has to be careful about ensuring that they invest in projects such as this while using open innovation to solve problems that can reasonably be outsourced.
The ability to predict power demand and match it to power supply is essential to the power industry, and Climate Connect’s business model is an interesting new way to approach this challenge. Previously, demand response companies like Johnson Controls (1) have served to address this gap for individual building owners but actively managing and arbitraging the mismatch between that building’s power demand and the cost of the power from the grid (which is determined by the supply/demand gap at the grid level). However, Climate Connect’s model would essentially eliminate the need for a company like Johnson Controls, but moving the management of power resources up to the grid level. Working in concert with battery storage technologies, AI like of Climate Connect would greatly facilitate the move to a 100% renewable world.
Regarding the concern about continued data sharing if companies build their own equivalent of Climate Connect technology in-house, I would argue that Climate Connect would be in a great position because they would be an attractive acquisition target for strategic companies such as utilities or grid operators who don’t want to have to build this technology themselves from the bottom up.
In theory, using machine learning to sort through data dumps can absolutely be additive to the journalistic process, as proven by the example of the Panama Papers cited above. Equally, the role of the reporter cannot be lost in this effort, and the more that journalists use AI, the more those journalists must build a secondary knowledge base to understand what exactly the algorithms they are using are doing. For instance, without proper direction, journalists might miss key insights in a data dump, and therefore assume that, because their algorithm did not return anything of interest, there is no story to pursue.
Additionally, if someone is creating algorithms to root out corruption, should that responsible agent be only journalists? If we are talking about countries or governments or corporations where the agent that would need to implement the technology would be the same agent under suspicion of corruption, then, perhaps, journalists are the appropriate actors to step in and fill the void. But, in the long term, governments could implement this technology themselves as a self-governance mechanism to discourage corruption, which seems a more appropriate place to lay the responsibility, than to leave it entirely to the “Fifth Estate.”