I don’t think financial compensation will be worthwhile for the current audience of engaged users at Zooniverse. Money is not a motivator on the list of Galaxy Zoo participants. Moving forward I think Zooniverse should consider dividing work into two streams. In the first stream it can have the more engaging tasks likely to result in the discoveries, pleasing images, and amazement that engage their current user base. In the second stream, I think they can have a separate team work-for-pay on the most mundane tasks or classifications. This division of work would allow them to maintain ongoing engagement with people interested in science and also increase their capacity to analyze data.
Even if they do implement a system like this, I agree that Zooniverse will need to do more to engage its audience in tasks beyond data processing. In the long term they will need to engage its audience with more meaningful research and projects to drive retention and collaboration on its platform.
I am not convinced 3D printing will become widely used for end-to-end homebuilding in the United States in the future. I think a core problem will be the need to deploy printers to one area and have them repeatedly print homes in that area. From my understanding, the economics only work if a machine sets up in one town and makes several hundred homes. I believe the problem here will be the municipality not wanting ICON to create a new neighborhood of low-cost homes. Unfortunately, low cost housing is not very popular in local municipalities as residents believe the addition of low-cost housing will hurt their own house value. If ICON is able to further diversify its offerings and add more upscale elements, they may be able to get past this impression.
Personally, I think I would love to live in a printed home, especially at those prices! They look cozy and simple. To entice me further, I would want to know more about the environmental impact of these homes or if they had a 1-for-1 program similar to TOMs. Perhaps by buying a printed home in the US I could fund a home for someone elsewhere in the world.
This application of machine learning is really interesting, and it is not something I had previously considered. Thinking about the ramifications that you have outlined I definitely believe that government regulation or monitoring is required to avoid future AI abuses. This is especially the case as large companies, independent actors, or even other countries benefit from the theft of private data or intellectual property. Small businesses may be left particularly vulnerable if government doesn’t create a framework for AI usage as the Darktrace software is very expensive.
My biggest concern is that this system may not be able to stop the biggest threat enterprises face: their employees. An algorithm might be able to be trained to detect a virus spreading but it may not be smart enough to prevent Joe in accounting from accidentally providing classified information to a spoofed email account.
In the case of LEGO, I am not sure the benefits of LEGO Ideas or LEGO Life outweigh the risks. There are obviously huge privacy implications. Unfortunately, there are people would want to target the young users of LEGO Life and any breeches of user information could spell disaster for LEGO. Additionally, like the comments have previously stated, I think LEGO’s strength are in its physical product. I don’t see LEGO Ideas or LEGO Life driving meaningful incremental sales that support the LEGO business overall. They may even undercut LEGO by turning fans towards other popular digital building platforms like Minecraft.
My other concern is how fans respond to rejected ideas of the LEGO Ideas platform. I would be curious as to how members feel after working on an idea on the LEGO Ideas platform if that idea doesn’t get selected for production. Would that cause these teens and adults to be disappointed and turn away from the brand? Since only 23 of 26,000 submissions have been accepted there may be a lot of frustrated enthusiasts.
This is an extremely interesting topic. I was excited to see that 3D printing is being applied to humanitarian crisis. I believe the power constraint could be mitigated through solar and/or utilization of local power generators. Many areas with unreliable central grids have businesses or homes that have gas powered generators. In the event of a national emergency these can likely be used to power the augmented manufacturing equipment. My main concern is how long a 3D printer would be useful in these contexts. In the first day or so after a disaster it doesn’t seem that it would be possible to setup a 3D printer with the shipping and training required. Likewise, after the first or second week, when some normalcy should be restored to the impacted area, I would question if a 3D printer would still be useful during long-term recovery. That leaves only a short window where I can see a deployed 3D printer having an outsized impact.
This is a really interesting application of machine learning in that it has a dual-purpose. It aims to helps the university and students as well. I don’t think younger people are as data-concerned as older people, so I think they might not receive too much push-back from this implementation. I think in this discovery phase collecting a large initial data-set makes sense as they are using anonymous data. I would hope with time that they are able to hone down the data points that they discover aren’t necessarily related to retention. Right now, the 800 factors that they collect data on seem unnecessarily high. I think it might assuage privacy critics if they are able to reduce the data points that are collected and only collect the information that is most related to retention. The other concern I have is what the school will do when they identify students who are at risk of dropping-out. Identifying at risk students earlier is important but overall, I think they need more robust strategies during the orientation phase in order for students to avoid becoming at-risk.