Image: Qiushi Fu
Humanity depends on technology more than ever before. We no longer remember phone numbers because we have everything saved on our phones, and we no longer use a map because we let a navigation app do the work for us. Machines have been taking over human roles since the industrial revolution, and with artificial intelligence (AI) systems, even complex roles could be done by machines. Would that be the case with design managers? And what does AI even mean?
AI: The Basics
Artificial Intelligence is a field in Computer Science that focuses on developing computers that can make informed decisions independently. The term artificial intelligence was first coined by Stanford researcher John McCarthy during the Dartmouth Conference in 1956. McCarthy defined the main mission of AI as making machines “use language, form abstractions and concepts, solve kinds of problems now reserved for humans, and improve themselves” (Hammond, 2015).
Although the term was coined 64 years ago, the real flourishing of AI started only recently. This happened for several reasons (Hammond, 2015; Kim et al., 2019):
- Increased availability of data – more accessible data helps to train AI by enabling it to learn from many examples.
- Increased computational resources – computers are cheaper, stronger and faster; hence, they can cope with huge amounts of data.
- Increased use of machine learning (e.g., deep learning) – we do not need to write rules for machines to follow. Instead, machines can be trained and learn these rules automatically.
The development of AI will require the openings of new jobs: trainers, explainers and sustainers (Wilson & Daugherty, 2018; WIRED, 2018): every AI system needs to be trained to behave the way it is supposed to. More people would be employed to take care of the AI’s training. If AI is used to help humans make decisions, experts would be employed to help explain the data analysis process done by the AI, preceding the outcome. By explaining the outcome, the explainers would promise the trust between humans and AI systems. Finally, more people will be hired to sustain AI systems. They would make sure the AI functions safely and ethically.
When thinking of AI, what comes to your mind? Do you think about C-3PO and R2D2 or do you think about Siri and Cortana? Well, AI is even more common than that. AI is also when Netflix gives you viewing recommendations according to your previous views, or when a word processor advises you on a better way to write your text.
Okay, now that we’ve covered the basics, let’s talk about design management.
Design Managers & AI
When it comes to design, it seems that there are three areas in which design managers could encounter AI in their daily work:
- Data-Driven Design – training AI as part of a design process to innovate new concepts.
- AI Product Design – working as part of a team designing an AI product.
- AI as an Assistant – using AI as an assistant, with the design manager as an end-user.
Three areas in which design managers could encounter AI in their daily work.
Data-Driven Design
AI can complement our abilities and help us work better and faster. The goal of many AI-powered systems is not to replace humans, but to collaborate with them. A collaboration in which an experienced human works with AI, trained by data about past successes and failures. AI will be able to give design managers relevant information that could inspire them to come up with innovative solutions.
One of the main parts of the design process, and our main challenge as design managers, is to come with a clear problem definition. Design managers would have to identify and find relevant data for the AI to train on according to that problem definition. Does the data exist and are available? It depends on the case. What is known for sure is the need to improve our skills when it comes to dealing with data, in order to solve customers’ pain points.
AI Product Design
When working on an AI product, design managers should be prepared to work with a diverse team. It requires the effort of people from many fields: data scientists, engineers, developers, designers, human behaviorists, and when it comes to ethics, even lawyers. It would probably put one of the main roles of design managers – integrating – to the test. In addition to the team being multidisciplinary, it should also be culturally-diverse: an AI system learns what we teach it. A diverse team tends to have a wider range of opinions and tends to be more sensitive to gender and culture bias. Cases where AI systems were unintentionally trained to be biased have happened in the past. For example, if an AI is trained to recognize people, but the database it learns from only contains men, women might not be recognized. Working with a diverse team can prevent this from happening.
Design managers would have to learn about the differences between classic human-computer interaction and human-AI interaction, which comes with new challenges and opportunities. For example, users will expect a regular computer to be consistent and predictable, while expecting AI to be less consistent as a result of learning and evolving over time. Part of this would also be about making the interaction with AI transparent, and decide how an AI product might explain itself to a user. If the process to an AI’s outcome is understandable, it could increase users’ adaptability to the product and loyalty to the company.
AI as an Assistant
https://www.youtube.com/watch?v=D5VN56jQMWM&feature=youtu.be
Virtual assistants can communicate with others to schedule appointments, while chatbots can provide information for many customers at the same time. AI systems are being trained to understand the context of the conversation, and even the tone of speaking, to provide better customer service (Wilson & Daugherty, 2018). AI might not be able to understand emotions entirely, but with the analysis of customers’ choices and behaviors, it could help cut down manpower and give critical feedback to design managers.
AI can help design managers be more flexible and offer product customization to customers. No more “Any customer can have a car painted any color that he wants, so long as it is black” (Henry Ford), thanks to the AI’s ability to adjust to changes. In addition, it could enhance customer delight by providing tailored experiences according to their past preferences (Wilson & Daugherty, 2018).
What’s Next?
Design managers are trained to cope with uncertainty and become familiar with innovative endeavors. AI is exactly it. We must adapt to innovations that could augment our abilities. In a way, we have to keep improving and evolving, the same way that AI systems do.
As design managers, we need to learn about AI and adapt our role accordingly: we need to discover what AI could help us do, what AI might not be able to do, find this gap and fill it. For example, while AI can analyze a large amount of data, it still cannot come up with original ideas without a human making the data available and defining specific parameters for it. Even better, design managers should be the ones to recognize AI as a trend that can add value to the business. If a specific business is not yet aware of the benefits of AI, design managers can be the ones pushing the business to be more AI-savvy.
So, should we be worried? Not if we’re prepared. As AI becomes a common tool to improve businesses and keep their competitive advantage, it is possible that soon we would all have the opportunity to work with AI systems. Norman (2013) sees the ability to collaborate with machines as an opportunity for humans to become smarter, faster and stronger. Machines and AI systems can free our minds from the small things that waste our time and allow us to focus on the important ones. We will still use our brains; it is just that the tasks will be different.
Want to start familiarizing with AI? Here is a good place to start: https://uxplanet.org/designer-friendly-resources-to-study-ai-and-machine-learning-1-6106e257faeb
Resources
Afshar, V. (2018). AI will transform product management. Retrieved from ZDNet: https://www.zdnet.com/article/ai-is-transforming-product-management/
Cossins, D. (2018). Discriminating algorithms: 5 times AI showed prejudice. Retrieved from NewScientist: https://www.newscientist.com/article/2166207-discriminating-algorithms-5-times-ai-showed-prejudice/
Dewalt, K. (2017). Product Manager is the Hardest AI Position to Fill. Retrieved from Prolego: https://blog.prolego.io/product-manager-is-the-hardest-ai-position-to-fill-9d753bf4cfcc
Hammond, K. (2015). Practical Artificial Intelligence for Dummies. Hoboken: Wiley.
Kim, S. G., Yoon, S. M., Yang, M., Choi, J., Akay, H., & Burnell, E. (2019). AI for design: Virtual design assistant. CIRP Annals, 68(1), 141-144.
Norman, D. (2013). The design of everyday things: Revised and expanded edition. Basic books.
Oh, J. (2019). Yes, AI Will Replace Designers. Retrieved from Medium: https://medium.com/microsoft-design/yes-ai-will-replace-designers-9d90c6e34502
Vorvoreanu, M., Amershi, S., & Collisson, P. (2019, March 5). Guidelines for Human-AI Interaction- Eighteen best practices for human-centered AI design. Retrieved from Medium: https://medium.com/microsoft-design/guidelines-for-human-ai-interaction-9aa1535d72b9
Wilson, H. J., & Daugherty, P. R. (2018). Collaborative intelligence: humans and AI are joining forces. Harvard Business Review, 96(4), 114-123.
WIRED (2018). AI and the Future of Work. Retrieved from WIRED: https://www.wired.com/wiredinsider/2018/04/ai-future-work/
Icon Credits
Thank you to Andrew Doane (Fisherman), alberto galindo (Funnal) and Oksana Latysheva (Robot head) from the Noun Project.
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Will all design managers be replaced by machines?
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The topic you choose is trending nowadays. Just three weeks ago, I saw the YouTube video of Meet Amelia which you included in your blog. Although I am still very skeptical about AI and all the machine learning notions, still I was excited to read your blog to find out more about AI.
The heading of your post is catchy, thus it was a compelling lead which attracted me, thus I was curious and at the same time interested to know if AI will replace the jobs of design managers, because as a future design managers, of course, I am interested to know what the future will look like concerning job prospects for me. So, I would say that you got me there.
As I mentioned earlier the topic is gaining popularity, it was very interesting seeing how you linked it to design management. Not knowing much about AI, it was good that you defined it very well, you also gave the Netflix viewing recommendations as an example, with the rest of the examples you introduced, that gave me an idea of what AI is and the entire package. The interpretations and definitions of the terms used were clear and understandable even with my limited knowledge on the topic, I can say that I am more aware of the topic than before.
I am certain that AI will be beneficial to us in the long run, but I am not sure if the side effects will not include millions of people losing their jobs. An example of human beings been easily replaceable by machines was seen after the industrial revolution. Nevertheless, you have inspired me to be more open to AI, and to also conduct more research into the topic.
I find the whole paper interesting and at the same time informative and engaging. The tone of the blog was calm but convincing, you also took a more holistic approach in conveying the message of how to design managers can work with AI, and the challenges which they might face.
Furthermore, your subheadings were concisely-structured and easy to follow, it helped me navigate through your thoughts. Moreover, your use of language and grammar was outstanding. It was also very interesting that you used enough keywords which you linked to your resources. You have also demonstrated that you have done a thorough research into the topic, this has made your blog appear more credible to me and as a reader, It made me believed that your arguments and ideas were not just based on a mere fantasy or speculations, but it was rather supported by enough literatures which were coherent to the topic.
To conclude, I would say that you are a very good writer, I can imagine that the topic might have been very complex nonetheless, you managed to pull it off. Well done Noah