When I think about crowdsourcing, I am always wary about quality of ideas or product. In this case, Vention is currently relying upon a small team of engineers to design most of the public assemblies; however, you argue that to push open innovation past being a nice add-on feature, they should increasingly encouraging more designers to join the community and add to the library. With this suggestion, Vention must also ensure they can maintain moderation a baseline design standard to ensure their customers are receiving high-quality products. Thus on one hand, Vention may benefit from a wider catalog and perhaps more complex set of designs, but they may also be negatively affected if they are not able to successfully vet out designs that do not meet a certain standard. Thus for a community like this to take off, Vention must focus on creating trust with their customer base – have they been able to do this to-date and what will they have to do to maintain this level of trust? Will they moderate the quality check on their own or will they have users self-moderate via reviews like Amazon?
Utilizing open innovation for SoundCloud to source their future of creative content consumption is an extremely interesting proposition. I would argue that open innovation is present in many of today’s stronger digital businesses, with the evolution of products being dictated by the changing use cases of users. As an example, YouTube noticed how creators began uploading singles to their platforms and users would listen to playlists of songs rather than watch videos; in other words, they began using YouTube as a music streaming platform rather than video streaming platform. With this observation and through additional user testing, YouTube launched its YouTube Music service and app. While this may not be a direct form of open innovation, I feel as though YouTube indirectly sourced the future of their content consumption through a bottoms-up approach, developing a product vision by monitoring both creator and user trends. With this example, I 100% believe SoundCloud, similar to YouTube, should take on this approach in their product development process; however, they have be clear about their differentiation from other streaming services, noticing how their specific users use SoundCloud differently from other similar services.
The impact of technology on creative industries, such as Chanel, is something that always grabs my attention. In high fashion, the heritage and craftsmanship of the artisans has traditionally been the driving force behind a brand’s reputation and the high price tag. This is something you mentioned as you said, “[Chanel]…traditionally relied on its storied artisans for its innovation.” But for Chanel, can 3D printing augment their current creative process, bringing productivity gains and cost efficiencies, without completely replacing the role of the artisan? I feel as though for this to happen, 3D printing should not be front and center for Chanel when talking about a specific collection or item, but rather it should be considered another tool in the toolbox for the artisans to create one of their pieces. With this, I do think Chanel can incorporate 3D printed apparel into its collections while sustaining its exclusive image and timeless designs. I am sure Chanel, over the years, has utilized other innovations in their manufacturing, prototyping, and production processes to-date but those innovations are not top of mind when we visit a Chanel store.
I find it inspirational when emerging technologies are applied to some of the world’s most challenging and socially important problems. New Story is doing just this but utilizing additive manufacturing to tackle the global housing crisis. However, I wonder if this may be a case where solving one problem creates another. The construction sector and other jobs tangential to constructing homes (plumbing, electricians, etc.) employ many workers throughout the globe, and often provide employment opportunities to those who are sometimes less educated and privileged. I am curious to understand how additive manufacturing may be similar to automation and robotics in that it may have a social benefit and bring more efficiency to a certain industry but at the cost of human labor opportunities. In the near term, you note that the construction process still requires infrastructure and finishes to be done after printing, which also means that some tradition labor opportunities still exist. However, I wonder how the jobs required to conduct additive manufacturing compare to those of typical home construction from a skills and quantity standpoint.
Both of your questions hit on the two most significant questions about autonomous vehicles, in my view. The second question is one that I find fascinating because it brings up the question of programming ethics into autonomous vehicles. Do you specifically pick to kill an elderly passenger over a child if one of the passengers has to be killed? In these instances, the computer scientists and engineers are essentially playing God in making such design choices. The interesting thing is that human drivers make these choices all the time; however they are often forgiven for “bad” split-second decisions, such as turning into another car rather than swerving to the side of the road. Fair or not, that same forgiveness most probably won’t translate to the engineering team behind autonomous vehicles because they don’t have to make a split-second decision but rather are spending years making such choices. Thus, in these instances, I can foresee car manufacturers having to take blame and repetitively explain the rationale behind these programming decisions as these unfortunate events occur in the early days of autonomous vehicles.
I have been interested in how sleepy industries, like agriculture, are adopting machine learning for quite a while now. While it is clear that machine learning can bring great productivity to such industries, I think you hit upon one of the bigger impediments when you explained, “Over the next decade, artificial intelligence startups, equipment manufacturers and agricultural producers will have to collaborate to locate inefficiencies in the farming process…” I am curious to know how agricultural producers capture data and, if they do capture such data, how granular and reliable is it. At the end of the day, the application of expensive technology like ML and robotics comes down to an ROI question, and you can only answer this question by analyzing how expensive of a pain-point is the problem compared to the cost of the solution. I have no doubt AI startups are excited to explore this question, and you show that John Deere is also excited to collaborate; but will agricultural producers be incentivized and excited to put in the time and effort to find such inefficiencies?