This open innovation topic is not new to organizations. I completely agree that they should clearly define the outsider innovator value in this context. Many silicon valley organizations run these kind of open innovation programs. One that I’ve been part of was specifically focused on finding software security bugs in code-base of Facebook, where they give out monetary awards to the outside innovators. 
I agree with many comments above that open innovation does open the gate for malicious attackers as well and hence BoC should protect their data (specially their IP) with utmost urgency and be very careful in execution of this open innovation program – always be highly critical of what you receive from the outside world.
The first thought that came to my mind – Can we apply this technology (after perfecting in the long-term) to developing countries where there is a mass population that still don’t have a roof over their head and sleep on streets or live in poorly constructed hazardous (and dangerous) houses?
I agree that there would be regulatory hurdles, but in developing countries those hurdles would be far more lower and would be much easier to get government buy-in than compared to US.
One thing that the article does not talk about is the quality/durability of the printed parts and safety of the overall vehicle made using 3D printing. In developing countries, where road traffic is very bad and accidents are a daily phenomenon, durability of the car and parts and more importantly safety of the people inside are more valuable. I completely agree to your point that car manufacturers should partner up with leading universities in 3D printing R&D but also include the durability aspect in their research as well. I think Ford’s investment on research of quality and durable 3D printed parts would give them a long-term advantage over their competitors (even if it is after 2030).
In my opinion, connecting patients with physicians is an important step in diagnosis of a problem. Machine learning can only go so far. In medical science, it’s not just diagnosis of the problem that could be the end of a user journey – it’s just the start. The human judgement that a physician brings to the table can never be replaced by a machine. Moreover, thinking about village areas in developing countries, services like Teladoc can be very useful where physician availability is almost zero and people are still relying on their age-old methods of treatment.
On the commercial side, an app with just machine learning algorithm ( similar to Teladoc, but not involving any human interaction) could be programmed to suggest the most expensive medicine on the market when there might be cheaper options available – which an average user might not be aware of.
I agree that machine learning powered apps/technology should assist the doctors or physicians but should never replace them.
Whenever I see words like personalization, the couple of things come to mind:
1 – What data (about the user) is being utilized to calculate that personalization effect on the app?
2 – How is that data being collected? Is it just the Taobao app data that is being used? Or is the app collecting data from other apps on the user’s phone?
I think the users are not realizing the reach of these apps in their personal life. There is a fine line between using user data and exploiting it for profits. Are there any regulations or data privacy laws in China to prevent misuse of this data being collected on users?
On other note, I agree with a lot of people above that the app does not know us better than ourselves. It just offers new products to a particular demographic. Its similar to a sales person introducing a new product to us on the street or in a retail shop. That does not mean that the sales person knows us better than ourselves.