Nowadays, the term “smart product” has become prominent in our daily life. I believe many of you can easily pull out a few items with the label “smart”. Thinking of how your smart phone can upgrade its program while you are sound asleep before dawn, it would probably not be difficult for you to understand that a product and its family will grow constantly and change into new fashions which are not the same as the one that you currently have in your hands. For now, the upgrades of smart products are more about software. You probably complain that upgraded programs don’t work as well as before. Have you ever imagined that your smart product can be changed into the style which you like? I’d like to say, yes, it can, as long as the contextual data of your every-day use can be decoded, applied and responded in a correct way.
When smart products have become the testing ground of technologies of Artificial Intelligent (AI) and Internet of Things (IoT), it would be hard to imagine the absence of AI in the development of a smart product. The design of smart products urgently needs the participation of AI to understand users better, to discover demands, and get inspirations, and importantly, to achieve these through the data. Therefore, in A3 I propose this new concept of AI Prototyping System for supporting Smart Product Development.
The design of smart products is also a collaborative learning process that aims at design innovation. In this course, I have learned a lot of fabulous online applications that can support collaboration, most of them apply to simple and conventional scenarios. I also hope mobile collaborative learning can play its role in more complicated, specialized scopes, such as in group problem solving and innovation. I think the design of smart products is a pretty good experimental ground in this aspect.
Here is my A3 presentation.
Hi Shirley
What an interesting topic! I think the idea of a “smart” topic has been attached to homes these days, so I was struggling to imagine a smart product that’s mobile aside from our phones. The idea of a smart process could certainly create many different products that could cater to the specific needs of the general population. My experience with being an educational assistant makes me think of this as the technology version of differentiating so that all users would be able to get their target experience out of the specific app. I would wonder how long it might be before potentially there are plans to turn this into something that we see daily? Are there any companies or organizations that are working towards building this sort of structure with a clear plan to implement in the near future?
Hi Shirley,
What a great project. I’m impressed. After going through your presentation I was so bought in that I wanted to learn more, so I did a search, found nothing, and then realized that this is your idea! Something like this doesn’t seem too far off. You make a good case for what needs to be sorted out: sorting through the large amounts of data, complexity of collaboration for the various designers, to name a few. Your point about the complexity of the end-user’s context stood out. That would be a tough one because if the device/software is functioning properly, how would it change, or evolve? Maybe all the data that is gathered from the users might give a signifier for a need to modify an aspect of that device or software. And, as I wrote this, I remember that you mentioned it in the “Why the Intelligent Prototyping System.”
I only have a little bit of knowledge in design, but I have to say that this project really piqued my interest to know more.
Thank you! Congratulations.
Mark
Hello Shirley,
This is a brilliant presentation! I wish I learned it two years ago when we pivoted the business to online Ed-Tech. It might have saved us a lot of effort and time to design our prototypes for our clients. The best part is the “dialogue” between the application and the user.
From your presentation, I think this could also be used by secondary students. They could also use it as a tool to learn how to design a smart product.
Hi Shirley,
I liked your presentation on Genially. The topic of IPS was a little hard for me to grasp without any examples, but I think that might just be due to my lack of experience in the design field. I liked your slide on “Why the Intelligent Prototyping System”, which outlined some very relevant steps in developing a product such has staying collaborative through mobile platforms and supporting group problem-solving by machine learning. If prototypes can be made cheaply and quickly, consumers can test out the prototype that has some actual functions and feedback in a more instant manner, then the cost of development would go down too. It would be a win-win situation.
Thanks for sharing! I enjoyed your presentation!
Emily
Hi Emily,
I am happy you like it. Thank you so much for sharing your comments. It was difficult to find an example, honestly, because this is a new conceptual proposal that I made. While I made this presentation, I even thought it would be easier to explain if I could make an actual system. I hope it can become true one day. As you say, the IPS, theoretically so far, can shorten the developing cycle and realize accurate, personalized functional positioning to the market.
Hi Shirley,
I like how well thought out your presentation is. I think that it is interesting to think about the design of Smart products, because it is something we often take for granted. I think that the diagram of IPS is great, because it helps the reader to visualize how user perceptions and needs drive innovation in Smart technology design. One thing I would look at is the use of algorithms to introduce objectivity. Algorithms are objective in the sense that they are formulaic, but they can also produce bias, as they reproduce what is most popular. Great job!
Jen
Hi Jen,
I am glad you like it, and thank you so much for your comments. When it comes to AI, I think it’s exactly a bit ironic. Humans create AI to augment natural intelligence of human selves. However, human biases can creep into AI sometimes. That is why AI scientists have been trying to mitigate bias in AI algorithms (https://hbr.org/2019/10/what-do-we-do-about-the-biases-in-ai).
Hi Shirley:
This is not bad. Having work in telecom smart products have been a tough sell. The biggest problems were the diversity of the consumer base, various provincial regulations restricting certain types of information for data collection, and the cost of infrastructure and skilled workforce labour power to run. Your A3 is very broad in scope so it is not possible to go in depth about these topics. The one thing I was surprised that was not mentioned was the consumer. The consumer is the heart of what drives the data. Without the consumer, what rational would any company have to collect data? What rational would exist to build anything, especially smart products. It’s something to really think about.
Hi Brittany, thank you very much for your comment.
You are right. Consumer data collection is exactly a big business behind technology. The business needs permissions from consumers, cross-section agreements and governments’ regulations. The reality is that data collection is already under way. It is just that we don’t know what type of data, and how much data is being collected and used safely and effectively. In my A3 assignment, I cast a future of data application between products and the design team.
In the field of product design, “consumer” and “user” are two distinguished terms; the term of consumer is the person who has the purchase behavior in the market, while the term of user refers to the actual user of the product. Sometimes, a consumer could be an actual user; but sometimes, a consumer is only a buyer, not a user. In my A3, the system is more focusing on acquiring the contextual data of uses, therefore I used the term of user rather than consumer. At the same time, as you mentioned, information from consumers is also important for the development. This part of information can be obtained from the marketer – one of participants of design.