Move 37

Designers make choices. They should be able to provide rationales for those choices. (Although sometimes they can’t.) Being able to explain the thinking that went into a design move to yourself, your teammates and clients is part of being a professional.

Move 37. This was the move AlphaGo made which took everyone by surprise because it appeared so wrong at first.

The interesting thing is that in hindsight it appeared AlphaGo had good reasons for this move. Based on a calculation of odds, basically.

If asked at the time, would AlphaGo have been able to provide this rationale?

It’s a thing that pops up in a lot of the reading I am doing around AI. This idea of transparency. In some fields you don’t just want an AI to provide you with a decision, but also with the arguments supporting that decision. Obvious examples would include a system that helps diagnose disease. You want it to provide more than just the diagnosis. Because if it turns out to be wrong, you want to be able to say why at the time you thought it was right. This is a social, cultural and also legal requirement.

It’s interesting.

Although lives don’t depend on it, the same might apply to intelligent design tools. If I am working with a system and it is offering me design directions or solutions, I want to know why it is suggesting these things as well. Because my reason for picking one over the other depends not just on the surface level properties of the design but also the underlying reasons. It might be important because I need to be able to tell stakeholders about it.

An added side effect of this is that a designer working with such a system is be exposed to machine reasoning about design choices. This could inform their own future thinking too.

Transparent AI might help people improve themselves. A black box can’t teach you much about the craft it’s performing. Looking at outcomes can be inspirational or helpful, but the processes that lead up to them can be equally informative. If not more so.

Imagine working with an intelligent design tool and getting the equivalent of an AlphaGo move 37 moment. Hugely inspirational. Game changer.

This idea gets me much more excited than automating design tasks does.

Artificial intelligence as partner

Some notes on artificial intelligence, technology as partner and related user interface design challenges. Mostly notes to self, not sure I am adding much to the debate. Just summarising what I think is important to think about more. Warning: Dense with links.

Matt Jones writes about how artificial intelligence does not have to be a slave, but can also be partner.

I’m personally much more interested in machine intelligence as human augmentation rather than the oft-hyped AI assistant as a separate embodiment.

I would add a third possibility, which is AI as master. A common fear we humans have and one I think only growing as things like AlphaGo and new Boston Dynamics robots keep happening.

I have had a tweet pinned to my timeline for a while now, which is a quote from Play Matters.

“tech­no­logy is not a ser­vant or a mas­ter but a source of expres­sion, a way of being”

So this idea actually does not just apply to AI but to tech in general. Of course, as tech gets smarter and more independent from humans, the idea of a ‘third way’ only grows in importance.

More tweeting. A while back, shortly after AlphaGo’s victory, James tweeted:

On the one hand, we must insist, as Kasparov did, on Advanced Go, and then Advanced Everything Else https://en.wikipedia.org/wiki/Advanced_Chess

Advanced Chess is a clear example of humans and AI partnering. And it is also an example of technology as a source of expression and a way of being.

Also, in a WIRED article on AlphaGo, someone who had played the AI repeatedly says his game has improved tremendously.

So that is the promise: Artificially intelligent systems which work together with humans for mutual benefit.

Now of course these AIs don’t just arrive into the world fully formed. They are created by humans with particular goals in mind. So there is a design component there. We can design them to be partners but we can also design them to be masters or slaves.

As an aside: Maybe AIs that make use of deep learning are particularly well suited to this partner model? I do not know enough about it to say for sure. But I was struck by this piece on why Google ditched Boston Dynamics. There apparently is a significant difference between holistic and reductionist approaches, deep learning being holistic. I imagine reductionist AI might be more dependent on humans. But this is just wild speculation. I don’t know if there is anything there.

This insistence of James on “advanced everything else” is a world view. A politics. To allow ourselves to be increasingly entangled with these systems, to not be afraid of them. Because if we are afraid, we either want to subjugate them or they will subjugate us. It is also about not obscuring the systems we are part of. This is a sentiment also expressed by James in the same series of tweets I quoted from earlier:

These emergences are also the best model we have ever built for describing the true state of the world as it always already exists.

And there is overlap here with ideas expressed by Kevin in ‘Design as Participation’:

[W]e are no longer just using computers. We are using computers to use the world. The obscured and complex code and engineering now engages with people, resources, civics, communities and ecosystems. Should designers continue to privilege users above all others in the system? What would it mean to design for participants instead? For all the participants?

AI partners might help us to better see the systems the world is made up of and engage with them more deeply. This hope is expressed by Matt Webb, too:

with the re-emergence of artificial intelligence (only this time with a buddy-style user interface that actually works), this question of “doing something for me” vs “allowing me to do even more” is going to get even more pronounced. Both are effective, but the first sucks… or at least, it sucks according to my own personal politics, because I regard individual alienation from society and complex systems as one of the huge threats in the 21st century.

I am reminded of the mixed-initiative systems being researched in the area of procedural content generation for games. I wrote about these a while back on the Hubbub blog. Such systems are partners of designers. They give something like super powers. Now imagine such powers applied to other problems. Quite exciting.

Actually, in the aforementioned article I distinguish between tools for making things and tools for inspecting possibility spaces. In the first case designers manipulate more abstract representations of the intended outcome and the system generates the actual output. In the second case the system visualises the range of possible outcomes given a particular configuration of the abstract representation. These two are best paired.

From a design perspective, a lot remains to be figured out. If I look at those mixed-initiative tools I am struck by how poorly they communicate what the AI is doing and what its capabilities are. There is a huge user interface design challenge there.

For stuff focused on getting information, a conversational UI seems to be the current local optimum for working with an AI. But for tools for creativity, to use the two-way split proposed by Victor, different UIs will be required.

What shape will they take? What visual language do we need to express the particular properties of artificial intelligence? What approaches can we take in addition to personifying AI as bots or characters? I don’t know and I can hardly think of any good examples that point towards promising approaches. Lots to be done.