Valentina Contini on AI in innovation, multi-potentiality, AI-augmented foresight, and personas from the future (AC Ep74)

“We don’t just give creative thinking to the AI, but we actually use the AI to make space for our own creative thinking.”

– Valentina Contini

About Valentina Contini

Valentina Contini is an innovation strategist for a global IT services firm, a technofuturist, and speaker. She has a background in engineering, innovation design, AI-powered foresight, and biohacking. Her previous work includes founding the Innovation Lab at Porsche.

Website:

Valentina Contini

LinkedIn Profile:

Valentina Contini

What you will learn

• Exploring the power of being a professional black sheep
• Using AI as a creative sparring partner
• Bridging the gap between ideas and visuals with AI tools
• Accelerating foresight processes through generative AI
• Unlocking human potential with AI-augmented creativity
• Envisioning immersive future scenarios with digital personas
• Embracing technology to make space for critical thinking

Episode Resources

People

• Leonardo da Vinci
• Refik Anadol

Companies

• NTT

Technical Terms

• AI (Artificial Intelligence)
• Generative AI
• Brain-computer interfaces
• Digital twin
• Futures wheel
• Speculative design
• Large language models (LLM)
• Quantum computing
• Decentralization

Transcript

Ross Dawson: Valentina, it’s awesome to have you on the show.

Valentina Contini: Oh, thank you. Thank you for inviting me here.

Ross: So, you call yourself a professional black sheep. That sounds like a good job to me. So what does that mean?

Valentina: On LinkedIn, a lot of people have very nice, amazing titles or super inspirational quotes. And for me, it was always like, what am I actually?

After a bit of thinking, I realized that wherever I am, I am actually always the one that is different. In the past, as a mechanical engineer, I was building cars for 15 years. That’s kind of weird if you are a woman, and also not really looking like the standard engineer.

Then I changed jobs, and I always ended up being the different one. I was in strategy consulting for a bit, and again, being an engineer in a strategy consulting role was the weird thing—it was not normal. So I’m always the weird one. I think that “professional black sheep” pretty much describes that.

Ross: Well, I think the future is in being weird. I mean, if you’re not weird, then you’re probably not gonna have a job. If you are weird, then you probably will.

Valentina: Yeah, definitely, definitely. I think that’s the main selling point right now.

Ross: So, innovation strategy, I think, is probably a reasonable description of a lot of what you do at the moment. Starting from that, you augment yourself in many ways—you augment your work and so on. How can we augment the process of innovating, making the new faster and better? What are the elements of that? What does that look like?

Valentina: I think a big part of it comes now thanks to AI, for a very specific reason. Since the pandemic, we are not really spending time in working environments together with other people in the same place.

There is less of this exchange that creates innovation and creativity or sparks something out of a random discussion. Generative AI, with the leap it made in the last year, is like your sparring partner that you always have without needing to be among other people.

What is interesting is that generative AI is not just one person—it’s collective knowledge from many people. It has many downsides as well, but focusing on this, I can access many people at the same time when I use a tool like generative AI.

Ross: So that’s, in a way, an individual tool. It’s a creative sparring partner or can augment our creativity. I think we can maybe come back to some of that in various ways, but thinking about an organizational level—going from individual creativity to an innovation process where the organization innovates—what are some of the other pieces of that puzzle?

Valentina: You can use it in many different steps of the way. I think another very important piece is using AI for automating easy, repetitive, and boring tasks so that employees have more time available for their creative thinking.

We don’t just give creative thinking to the AI, but we actually use the AI to make space for our own creative thinking.

I also believe that what is very interesting is I have a very visual brain. In my mind, there are always images of what I envision for the future—whether as a product or an idea. Tools like AI image generators can bridge this gap between the images in my brain and showing other people those images.

I think that’s a very powerful way to actually augment or enhance our capabilities.

Ross: Just on that, though—you are an illustrator as well, correct?

Valentina: Not really. What I’m now working on is a project where we create future scenarios. The narrative is very important, but at the same time, it’s difficult to understand what the future is if you cannot see it.

I use these tools to generate images of the future—products, advertisements, or speculative design. That’s something I would have never been able to do without generative AI tools. It would have taken me years of learning a new skill to make these designs myself.

With this, I just spent two hours chatting with the tool, and the images I wanted came out pretty much on their own. It’s really an incredible paradigm shift because you can acquire new skills without acquiring them.

Ross: Yes, let’s dig into that AI-augmented foresight. Foresight is a discipline with many facets to how it’s done in a thorough way.

Obviously, one element is being able to show people what those futures look like. But where are you seeing or applying tools to augment the foresight process?

Valentina: It’s a topic that I started looking into about two years ago, when GPT-3.5 was out. I was always a bit annoyed that a process like generating scenarios for a company would take so much time. You needed to involve many different people, experts, and stakeholders.

It was a bit frustrating because it’s also the reason why it gets done only once every 3, 4, or 5 years—not more often. In a world where everything changes so fast, doing it just every five years is not enough.

I started experimenting with AI, and there are many methodologies where AI can play to its strengths. For example, a futures wheel, where you would normally need many people to come up with different perspectives on impacts and second-degree impacts. AI is good at looking at large amounts of data and finding connections.

Humans are always filtered by their own bias—in a positive sense. We have our own baggage, education, and culture. AI, on the other hand, brings in a collective bias. It brings many perspectives, though it still depends on where the AI was developed and which data was used to train it.

For example, the bias might lean more Western, Eastern, privileged, or otherwise. But that’s a specific part of the process where AI is extremely helpful.

Of course, you cannot take out critical thinking from the human. AI is just a tool. The human in the loop evaluates the results with critical thinking, deciding if what AI produces is usable or complete nonsense.

Ross: So, thinking about scenarios, one of the outcomes of a scenario process is broadly twofold. First, you have a set of scenarios that you can use to identify strategic options, test strategies, and explore other possibilities.

Second, an important outcome is the changed thinking of those people who participated in the process. If you delegate too much of that to the AI, you just get the scenarios without the benefit of the changed thinking.

Are there ways to use AI-augmented foresight so humans start to think more diversely through the process?

Valentina: It’s always a matter of who you are involving and why you are creating the scenarios. What I find very interesting is when I create scenarios with someone who has never used AI for this kind of exercise.

The realization is often, “Oh wow, I could have never come to this point by myself in a thousand years.” It’s true that the attention goes to the tool, but at the same time, people pay so much attention to the results because they’re a bit scared of the tool. This shift in thinking already starts happening.

For example, I was working with a