Today is the first official work day of my new doctoral researcher position at Delft University of Technology. After more than two years of laying the ground work, I’m starting out on a new challenge.
I remember sitting outside a Jewel coffee bar in Singapore1 and going over the various options for whatever would be next after shutting down Hubbub. I knew I wanted to delve into the impact of machine learning and data science on interaction design. And largely through process of elimination I felt the best place for me to do so would be inside of academia.
Back in the Netherlands, with help from Ianus Keller, I started making inroads at TU Delft, my first choice for this kind of work. I had visited it on and off over the years, coaching students and doing guest lectures. I’d felt at home right away.
There were quite a few twists and turns along the way but now here we are. Starting this month I am a doctoral candidate at Delft University of Technology’s faculty of Industrial Design Engineering.
Below is a first rough abstract of the research. But in the months to come this is likely to change substantially as I start hammering out a proper research plan. I plan to post the occasional update on my work here, so if you’re interested your best bet is probably to do the old RSS thing. There’s social media too, of course. And I might set up a newsletter at some point. We’ll see.
If any of this resonates, do get in touch. I’d love to start a conversation with as many people as possible about this stuff.
Intelligibility and Transparency of Smart Public Infrastructures: A Design Oriented Approach
This phd will explore how designers, technologists, and citizens can utilize rapid urban manufacturing and IoT technologies for designing urban space that expresses its intelligence from the intersection of people, places, activities and technology, not merely from the presence of cutting-edge technology. The key question is how smart public infrastructure, i.e. data-driven and algorithm-rich public infrastructures, can be understood by lay-people.
The design-oriented research will utilize a ‘research through design’ approach to develop a digital experience around the bridge and the surrounding urban space. During this extended design and making process the phd student will conduct empirical research to investigate design choices and their implications on (1) new forms of participatory data-informed design processes, (2) the technology-mediated experience of urban space, (3) the emerging relationship between residents and “their” bridge, and (4) new forms of data-informed, citizen led governance of public space.
My Foursquare history and 750 Words archive tell me this was on Saturday, January 16, 2016. [↩]
At a recent Tech Solidarity NL meetup we dove into Value Sensitive Design. This approach had been on my radar for a while so when we concluded that for our community it would be useful to talk about how to practice ethical design and development of technology, I figured we should check it out.
Value Sensitive Design has been around for ages. The earliest article I came across is by Batya Friedman in a 1996 edition of Interactions magazine. Ironically, or tragically, I must say I have only heard about the approach from academics and design theory nerds. In industry at large, Value Sensitive Design appears to be—to me at least—basically unknown. (A recent exception would be this interesting marriage of design sprints with Value Sensitive Design by Cennydd Bowles.)
For the meetup, I read a hand-full of papers and cobbled together a deck which attempts to summarise this ’framework’—the term favoured by its main proponents. I went through it and then we had a spirited discussion of how its ideas apply to our daily practice. A report of all of that can be found over at the Tech Solidarity NL website.
Below, I have attempted to pull together the most salient points from what is a rather dense twenty-plus-slides deck. I hope it is of some use to those professional designers and developers who are looking for better ways of building technology that serves the interest of the many, not the few.
What follows is mostly adapted from the chapter “Value Sensitive Design and Information Systems” in Human–computer interaction in management information systems: Foundations. All quotes are from there unless otherwise noted.
Background
The departure point is the observation that “there is a need for an overarching theoretical and methodological framework with which to handle the value dimensions of design work.” In other words, something that accounts for what we already know about how to deal with values in design work in terms of theory and concepts, as well as methods and techniques.
This is of course not a new concern. For example, famed cyberneticist Norbert Wiener argued that technology could help make us better human beings, and create a more just society. But for it to do so, he argued, we have to take control of the technology.
We have to reject the “worshiping [of] the new gadgets which are our own creation as if they were our masters.” (Wiener 1953)
We can find many more similar arguments throughout the history of information technology. Recently such concerns have flared up in industry as well as society at large. (Not always for the right reasons in my opinion, but that is something we will set aside for now.)
To address these concerns, Value Sensitive Design was developed. It is “a theoretically grounded approach to the design of technology that accounts for human values in a principled and comprehensive manner throughout the design process.” It has been applied successfully for over 20 years.
Defining Values
But what is a value? In the literature it is defined as “what a person or group of people consider important in life.” I like this definition because it is easy to grasp but also underlines the slippery nature of values. Some things to keep in mind when talking about values:
In a narrow sense, the word “value” refers simply to the economic worth of an object. This is not the meaning employed by Value Sensitive Design.
Values should not be conflated with facts (the “fact/value distinction”) especially insofar as facts do not logically entail value.
“Is” does not imply “ought” (the naturalistic fallacy).
Values cannot be motivated only by an empirical account of the external world, but depend substantively on the interests and desires of human beings within a cultural milieu. (So contrary to what some right-wingers like to say: “Facts do care about your feelings.”)
Investigations
Let’s dig into the way this all works. “Value Sensitive Design is an iterative methodology that integrates conceptual, empirical, and technical investigations.” So it distinguishes between three types of activities (“investigations”) and it prescribes cycling through these activities multiple times. Below are listed questions and notes that are relevant to each type of investigation. But in brief, this is how I understand them:
Defining the specific values at play in a project;
Observing, measuring, and documenting people’s behaviour and the context of use;
Analysing the ways in which a particular technology supports or hinders particular values.
Conceptual Investigations
Who are the direct and indirect stakeholders affected by the design at hand?
How are both classes of stakeholders affected?
What values are implicated?
How should we engage in trade-offs among competing values in the design, implementation, and use of information systems (e.g., autonomy vs. security, or anonymity vs. trust)?
Should moral values (e.g., a right to privacy) have greater weight than, or even trump, non-moral values (e.g., aesthetic preferences)?
Empirical Investigations
How do stakeholders apprehend individual values in the interactive context?
How do they prioritise competing values in design trade-offs?
How do they prioritise individual values and usability considerations?
Are there differences between espoused practice (what people say) compared with actual practice (what people do)?
And, specifically focusing on organisations:
What are organisations’ motivations, methods of training and dissemination, reward structures, and economic incentives?
Technical Investigations
Not a list of questions here, but some notes:
Value Sensitive Design takes the position that technologies in general, and information and computer technologies in particular, have properties that make them more or less suitable for certain activities. A given technology more readily supports certain values while rendering other activities and values more difficult to realise.
Technical investigations involve the proactive design of systems to support values identified in the conceptual investigation.
Technical investigations focus on the technology itself. Empirical investigations focus on the individuals, groups, or larger social systems that configure, use, or are otherwise affected by the technology.
Value Sensitive Design enlarges the arena in which values arise to include not only the work place
Value Sensitive Design contributes a unique methodology that employs conceptual, empirical, and technical investigations, applied iteratively and integratively
Value Sensitive Design enlarges the scope of human values beyond those of cooperation (CSCW) and participation and democracy (Participatory Design) to include all values, especially those with moral import.
Value Sensitive Design distinguishes between usability and human values with ethical import.
Value Sensitive Design identifies and takes seriously two classes of stakeholders: direct and indirect.
Value Sensitive Design is an interactional theory
Value Sensitive Design builds from the psychological proposition that certain values are universally held, although how such values play out in a particular culture at a particular point in time can vary considerably
[ad 4] “By moral, we refer to issues that pertain to fairness, justice, human welfare and virtue, […] Value Sensitive Design also accounts for conventions (e.g., standardisation of protocols) and personal values”
[ad 5] “Usability refers to characteristics of a system that make it work in a functional sense, […] not all highly usable systems support ethical values”
[ad 6] “Often, indirect stakeholders are ignored in the design process.”
[ad 7] “values are viewed neither as inscribed into technology (an endogenous theory), nor as simply transmitted by social forces (an exogenous theory). […] the interactional position holds that while the features or properties that people design into technologies more readily support certain values and hinder others, the technology’s actual use depends on the goals of the people interacting with it. […] through human interaction, technology itself changes over time.”
[ad 8] “the more concretely (act-based) one conceptualises a value, the more one will be led to recognising cultural variation; conversely, the more abstractly one conceptualises a value, the more one will be led to recognising universals”
How-To
Value Sensitive Design doesn’t prescribe a particular process, which is fine by me, because I believe strongly in tailoring your process to the particular project at hand. Part of being a thoughtful designer is designing a project’s process as well. However, some guidance is offered for how to proceed in most cases. Here’s a list, plus some notes.
Start with a value, technology, or context of use
Identify direct and indirect stakeholders
Identify benefits and harms for each stakeholder group
Map benefits and harms onto corresponding values
Conduct a conceptual investigation of key values
Identify potential value conflicts
Integrate value considerations into one’s organisational structure
[ad 1] “We suggest starting with the aspect that is most central to your work and interests.”
[ad 2] “direct stakeholders are those individuals who interact directly with the technology or with the technology’s output. Indirect stakeholders are those individuals who are also impacted by the system, though they never interact directly with it. […] Within each of these two overarching categories of stakeholders, there may be several subgroups. […] A single individual may be a member of more than one stakeholder group or subgroup. […] An organisational power structure is often orthogonal to the distinction between direct and indirect stakeholders.”
[ad 3] “one rule of thumb in the conceptual investigation is to give priority to indirect stakeholders who are strongly affected, or to large groups that are somewhat affected […] Attend to issues of technical, cognitive, and physical competency. […] personas have a tendency to lead to stereotypes because they require a list of “socially coherent” attributes to be associated with the “imagined individual.” […] we have deviated from the typical use of personas that maps a single persona onto a single user group, to allow for a single persona to map onto to multiple stakeholder groups”
[ad 4] “In some cases, the corresponding values will be obvious, but not always.”
[ad 5] “the philosophical ontological literature can help provide criteria for what a value is, and thereby how to assess it empirically.”
[ad 6] “value conflicts should usually not be conceived of as “either/or” situations, but as constraints on the design space.”
[ad 7] “In the real world, of course, human values (especially those with ethical import) may collide with economic objectives, power, and other factors. However, even in such situations, Value Sensitive Design should be able to make positive contributions, by showing alternate designs that better support enduring human values.”
Considering Values
Human values with ethical import often implicated in system design
This table is a useful heuristic tool for values that might be considered. The authors note that it is not intended as a complete list of human values that might be implicated. Another more elaborate tool of a similar sort are the Envisioning Cards.
For the ethics nerds, it may be interesting to note that most of the values in this table hinge on the deontological and consequentialist moral orientations. In addition, the authors have chose several other values related to system design.
Interviewing Stakeholders
When doing the empirical investigations you’ll probably rely on stakeholder interviews quite heavily. Stakeholder interviews shouldn’t be a new thing to any design professional worth their salt. But the authors do offer some practical pointers to keep in mind.
First of all, keep the interview somewhat open-ended. This means conducting a semi-structured interview. This will allow you to ask the things you want to know, but also creates the opportunity for new and unexpected insights to emerge.
Laddering—repeatedly asking the question “Why?” can get you quite far.
The most important thing, before interviewing stakeholders, is to have a good understanding of the subject at hand. Demarcate it using criteria that can be explained to outsiders. Use descriptions of issues or tasks for participants to engage in, so that the subject of the investigation becomes more concrete.
Technical Investigations
Two things I find interesting here. First of all, we are encouraged to map the relationship between design trade-offs, value conflicts and stakeholder groups. The goal of this exercise is to be able to see how stakeholder groups are affected in different ways.
The second useful suggestion for technical investigations is to build flexibility into a product or service’s technical infrastructure. The reason for this is that over time, new values and value conflicts can emerge. As designers we are not always around anymore once a system is deployed so it is good practice to enable the stakeholders to adapt our design to their evolving needs. (I was very much reminded of the approach advocated by Stewart Brand in How Buildings Learn.)
Conclusion
When discussing matters of ethics in design with peers I often notice a reluctance to widen the scope of our practice to include these issues. Frequently, folks argue that since it is impossible to foresee all the potential consequences of design choices, we can’t possibly be held accountable for all the terrible things that can happen as a result of a new technology being introduced into society.
I think that’s a misunderstanding of what ethical design is about. We may not always be directly responsible for the consequences of our design (both good and bad). But we are responsible for what we choose to make part of our concerns as we practice design. This should include the values considered important by the people impacted by our designs.
In the 1996 article mentioned at the start of this post, Friedman concludes as follows:
“As with the traditional criteria of reliability, efficiency, and correctness, we do not require perfection in value-sensitive design, but a commitment. And progress.” (Friedman 1996)
I think that is an apt place to end it here as well.
Friedman, Batya, Peter Kahn, and Alan Borning. “Value sensitive design: Theory and methods.” University of Washington technical report (2002): 02–12.
Le Dantec, Christopher A., Erika Shehan Poole, and Susan P. Wyche. “Values as lived experience: evolving value sensitive design in support of value discovery.” Proceedings of the SIGCHI conference on human factors in computing systems.ACM, 2009.
Borning, Alan, and Michael Muller. “Next steps for value sensitive design.” Proceedings of the SIGCHI conference on human factors in computing systems.ACM, 2012.
Freidman, B., P. Kahn, and A. Borning. “Value sensitive design and information systems.” Human–computer interaction in management information systems: Foundations (2006): 348–372.
Returning to what is something of an annual tradition, these are the books I’ve read in 2017. I set myself the goal of getting to 36 and managed 38 in the end. They’re listed below with some commentary on particularly memorable or otherwise noteworthy reads. To make things a bit more user friendly I’ve gone with four broad buckets although as you’ll see within each the picks range across genres and subjects.
Fiction
I always have one piece of fiction or narrative non-fiction going. I have a long-standing ‘project’ of reading cult classics. I can’t settle on a top pick for the first category so it’s going to have to be a tie between Lowry’s alcohol-drenched tale of lost love in pre-WWII Mexico, and Salter’s unmatched lyrical prose treatment of a young couple’s liaisons as imagined by a lecherous recluse in post-WWII France.
When I feel like something lighter I tend to seek out sci-fi written from before I was born. (Contemporary sci-fi more often than not disappoints me with its lack of imagination, or worse, nostalgia for futures past. I’m looking at you, Cline.) My top pick here would be the Strugatsky brothers, who blew me away with their weird tale of a world forever changed by the inexplicable visit by something truly alien.
I’ve also continued to seek out works by women, although I’ve been less strict with myself in this department than previous years. Here I’m ashamed to admit it took me this long to finally read anything by Woolf because Mrs Dalloway is every bit as good as they say it is. I recommend seeking out the annotated Penguin addition for additional insights into the many things she references.
I’ve also sometimes picked up a newer book because it popped up on my radar and I was just really excited about reading it. Most notably Dolan’s retelling of the Iliad in all its glorious, sad and gory detail, updated for today’s sensibilities.
Each time I read a narrative treatment of history or current affairs I feel like I should be doing more of it. All of these are recommended but Kapuściński towers over all with his heart-wrenching first-person account of the Iranian revolution.
A few books on design and technology here, although most of my ‘professional’ reading was confined to academic papers this year. I find those to be a more effective way of getting a handle on a particular subject. Books published on my métier are notoriously fluffy. I’ll point out Löwgren for a tough but rewarding read on how to do interaction design in a non-dogmatic but reflective way.
I got into leftist politics quite heavily this year and tried to educate myself a bit on contemporary anti-capitalist thinking. Fisher’s book is a most interesting and also amusing diagnosis of the current political and economic world system through a cultural lens. It’s a shame he’s no longer with us, I wonder what he would have made of recent events.
I decided to work my way through a bunch of roleplaying game books all ‘powered by the apocalypse’ – a family of games which I have been aware of for quite a while but haven’t had the opportunity to play myself. I like reading these because I find them oddly inspirational for professional purposes. But I will point to the original Apocalypse World as the one must-read as Baker remains one of the designers I am absolutely in awe of for the ways in which he manages to combine system and fiction in truly inventive ways.
The Perilous Wilds, Jason Lutes
Urban Shadows: Political Urban Fantasy Powered by the Apocalypse, Andrew Medeiros
Dungeon World, Sage LaTorra
Apocalypse World, D. Vincent Baker
Poetry
I don’t usually read poetry for reasons similar to how I basically stopped reading comics earlier: I can’t seem to find a good way of discovering worthwhile things to read. The collection below was a gift, and a delightful one.
As always, I welcome suggestions for what to read next. I’m shooting for 36 again this year and plan to proceed roughly as I’ve been doing lately—just meander from book to book with a bias towards works that are non-anglo, at least as old as I am, and preferably weird or inventive.
Earlier this year I coached Design for Interaction master students at Delft University of Technology in the course Research Methodology. The students organised three seminars for which I provided the claims and assigned reading. In the seminars they argued about my claims using the Toulmin Model of Argumentation. The readings served as sources for backing and evidence.
The claims and readings were all related to my nascent research project about machine learning. We delved into both designing for machine learning, and using machine learning as a design tool.
Below are the readings I assigned, with some notes on each, which should help you decide if you want to dive into them yourself.
The only non-academic piece in this list. This served the purpose of getting all students on the same page with regards to what machine learning is, its applications of machine learning in interaction design, and common challenges encountered. I still can’t think of any other single resource that is as good a starting point for the subject as this one.
Fiebrink’s Wekinator is groundbreaking, fun and inspiring so I had to include some of her writing in this list. This is mostly of interest for those looking into the use of machine learning for design and other creative and artistic endeavours. An important idea explored here is that tools that make use of (interactive, supervised) machine learning can be thought of as instruments. Using such a tool is like playing or performing, exploring a possibility space, engaging in a dialogue with the tool. For a tool to feel like an instrument requires a tight action-feedback loop.
A really good survey of how designers currently deal with machine learning. Key takeaways include that in most cases, the application of machine learning is still engineering-led as opposed to design-led, which hampers the creation of non-obvious machine learning applications. It also makes it hard for designers to consider ethical implications of design choices. A key reason for this is that at the moment, prototyping with machine learning is prohibitively cumbersome.
The second Fiebrink piece in this list, which is more of a deep dive into how people use Wekinator. As with the chapter listed above this is required reading for those working on design tools which make use of interactive machine learning. An important finding here is that users of intelligent design tools might have very different criteria for evaluating the ‘correctness’ of a trained model than engineers do. Such criteria are likely subjective and evaluation requires first-hand use of the model in real time.
Bostrom, Nick, and Eliezer Yudkowsky. 2014. “The Ethics of Artificial Intelligence.” In The Cambridge Handbook of Artificial Intelligence, edited by Keith Frankish and William M Ramsey, 316–34. Cambridge: Cambridge University Press. doi:10.1017/CBO9781139046855.020.
Bostrom is known for his somewhat crazy but thoughtprovoking book on superintelligence and although a large part of this chapter is about the ethics of general artificial intelligence (which at the very least is still a way out), the first section discusses the ethics of current “narrow” artificial intelligence. It makes for a good checklist of things designers should keep in mind when they create new applications of machine learning. Key insight: when a machine learning system takes on work with social dimensions—tasks previously performed by humans—the system inherits its social requirements.
Finally, a feet-in-the-mud exploration of what it actually means to design for machine learning with the tools most commonly used by designers today: drawings and diagrams of various sorts. In this case the focus is on using machine learning to make an interface adaptive. It includes an interesting discussion of how to balance the use of implicit and explicit user inputs for adaptation, and how to deal with inference errors. Once again the limitations of current sketching and prototyping tools is mentioned, and related to the need for designers to develop tacit knowledge about machine learning. Such tacit knowledge will only be gained when designers can work with machine learning in a hands-on manner.
Supplemental material
Floyd, Christiane. 1984. “A Systematic Look at Prototyping.” In Approaches to Prototyping, 1–18. Berlin, Heidelberg: Springer Berlin Heidelberg. doi:10.1007/978–3–642–69796–8_1.
I provided this to students so that they get some additional grounding in the various kinds of prototyping that are out there. It helps to prevent reductive notions of prototyping, and it makes for a nice complement to Buxton’s work on sketching.
Some of the papers refer to machine learning as a “design material” and this paper helps to understand what that idea means. Software is a material without qualities (it is extremely malleable, it can simulate nearly anything). Yet, it helps to consider it as a physical material in the metaphorical sense because we can then apply ways of design thinking and doing to software programming.
This is not exactly a now page, but I thought I would write up what I am doing at the moment since last reporting on my status in my end-of-year report.
The majority of my workdays are spent doing freelance design consulting. My primary gig has been through Eend at the Dutch Victim Support Foundation, where until very recently I was part of a team building online services. I helped out with product strategy, setting up a lean UX design process, and getting an integrated agile design and development team up and running. The first services are now shipping so it is time for me to move on, after 10 months of very gratifying work. I really enjoy working in the public sector and I hope to be doing more of it in future.
So yes, this means I am available and you can hire me to do strategy and design for software products and services. Just send me an email.
Shortly before the Dutch national elections of this year, Iskander and I gathered a group of fellow tech workers under the banner of “Tech Solidarity NL” to discuss the concerning lurch to the right in national politics and what our field can do about it. This has developed into a small but active community who gather monthly to educate ourselves and develop plans for collective action. I am getting a huge boost out of this. Figuring out how to be a leftist in this day and age is not easy. The only way to do it is to practice and for that reflection with peers is invaluable. Building and facilitating a group like this is hugely educational too. I have learned a lot about how a community is boot-strapped and nurtured.
And finally, the last major thing on my plate is a continuing effort to secure a PhD position for myself. I am getting great support from people at Delft University of Technology, in particular Gerd Kortuem. I am focusing on internet of things products that have features driven by machine learning. My ultimate aim is to develop prototyping tools for design and development teams that will help them create more innovative and more ethical solutions. The first step for this will be to conduct field research inside companies who are creating such products right now. So I am reaching out to people to see if I can secure a reasonable amount of potential collaborators for this, which will go a long way in proving the feasibility of my whole plan.
If you know of any companies that develop consumer-facing products that have a connected hardware component and make use of machine learning to drive features, do let me know.
That’s about it. Freelance UX consulting, leftist tech-worker organising and design-for-machine-learning research. Quite happy with that mix, really.
A few weeks ago I facilitated a discussion on ‘advocacy in a post-truth era’ at the European Digital Rights Initiative’s annual general assembly. And last night I was part of a discussion on fake news at a behaviour design meetup in Amsterdam. This was a good occasion to pull together some of my notes and figure out what I think is true about the ‘fake news’ phenomenon.
There is plenty of good writing out there exploring the history and current state of post-truth political culture.
Kellyanne Conway’s “alternative facts” and Michael Gove’s “I think people have had enough of experts” are just two examples of the right’s appropriation of what I would call epistemological relativism. Post-modernism was fun while it worked to advance our leftist agenda. But now that the tables are turned we’re not enjoying it quite as much anymore, are we?
Part of the fact-free politics playbook goes back at least as far as big tobacco’s efforts to discredit the anti-smoking lobby. “Doubt is our product” still applies to modern day reactionary movements such as climate change deniers and anti-vaxers.
The double whammy of news industry commercialisation and internet platform consolidation has created fertile ground for coordinated efforts by various groups to turn the sowing of doubt all the way up to eleven.
There is Russia’s “firehose of falsehood” which sends a high volume of messages across a wide range of channels with total disregard for truth or even consistency in a rapid, continuous and repetitive fashion. They seem to be having fun destabilising western democracies — including the Netherlands — without any apparent end-goal in mind.
And then there is the outrage marketing leveraged by trolls both minor and major. Pissing off mainstream media builds an audience on the fringes and in the underground. Journalists are held hostage by figures such as Milo because they depend on stories that trigger strong emotions for distribution, eyeballs, clicks and ultimately revenue.
So, given all of this, what is to be done? First some bad news. Facts, the weapon of choice for liberals, don’t appear to work. This is empirically evident from recent events, but it also appears to be borne out by psychology.
Facts are often more complicated than the untruths they are supposed to counter. It is also easier to remember a simple lie than a complicated truth. Complicating matters further, facts tend to be boring. Finally, and most interestingly, there is something called the ‘backfire effect’: we become more entrenched in our views when confronted with contradicting facts, because they are threatening to our group identities.
More bad news. Given the speed at which falsehoods spread through our networks, fact-checking is useless. Fact-checking is after-the-fact-checking. Worse, when media fact-check falsehoods on their front pages they are simply providing even more airtime to them. From a strategic perspective, when you debunk, you allow yourself to be captured by your opponent’s frame, and you’re also on the defensive. In Boydian terms you are caught in their OODA loop, when you should be working to take back the initiative, and you should be offering an alternative narrative.
I am not hopeful mainstream media will save us from these dynamics given the realities of the business models they operate inside of. Journalists inside of these organisations are typically overworked, just holding on for dear life and churning out stories at a rapid clip. In short, there is no time to orient and manoeuvre. For bad-faith actors, they are sitting ducks.
What about literacy? If only people knew about churnalism, the attention economy, and filter bubbles ‘they’ would become immune to the lies peddled by reactionaries and return to the liberal fold. Personally I find these claims highly unconvincing not to mention condescending.
My current working theory is that we, all of us, buy into the stories that activate one or more of our group identities, regardless of wether they are fact-based or outright lies. This is called ‘motivated reasoning’. Since this is a fact of psychology, we are all susceptible to it, including liberals who are supposedly defenders of fact-based reasoning.
Seriously though, what about literacy? I’m sorry, no. There is evidence that scientific literacy actually increases polarisation. Motivated reasoning trumps factual knowledge you may have. The same research shows however that curiosity in turn trumps motivated reasoning. The way I understand the distinction between literacy and curiosity is that the former is about knowledge while the latter is about attitude. Motivated reasoning isn’t counteracted by knowing stuff, but by wanting to know stuff.
This is a mixed bag. Offering facts is comparatively easy. Sparking curiosity requires storytelling which in turn requires imagination. If we’re presented with a fact we are not invited to ask questions. However, if we are presented with questions and those questions are wrapped up in stories that create emotional stakes, some of the views we hold might be destabilised.
In other words, if doubt is the product peddled by our opponents, then we should start trafficking in curiosity.
If you work in the field of design or artificial intelligence and are interested in exploring the opportunities at their intersection, consider yourself invited to an informal coffee meetup on February 15, 10am at Brix in Amsterdam.
Erik van der Pluijm and myself have for a while now been carrying on a conversation about AI and design and we felt it was time to expand the circle a bit. We are very curious who else out there shares our excitement.
Questions we are mulling over include: How does the design process change when creating intelligent products? And: How can teams collaborate with intelligent design tools to solve problems in new and interesting ways?
Anyway, lots to chew on.
No need to sign up or anything, just show up and we’ll see what happens.
Some notes on what I think I understand about technology and inequality.
Let’s start with an obvious big question: is technology destroying jobs faster than they can be replaced? On the long term the evidence isn’t strong. Humans always appear to invent new things to do. There is no reason this time around should be any different.
But in the short term technology has contributed to an evaporation of mid-skilled jobs. Parts of these jobs are automated entirely, parts can be done by fewer people because of higher productivity gained from tech.
My hunch is that we’ve seen an emergence of a new class of pseudo-monopolies. Oligopolies. And this is compounded by a ‘winner takes all’ dynamic that technology seems to produce.
Historically, looking at previous technological upsets, it appears education makes a big difference. People negatively affected by technological progress should have access to good education so that they have options. In the US the access to high quality education is not equally divided.
Apparently family income is associated with educational achievement. So if your family is rich, you are more likely to become a high skilled individual. And high skilled individuals are privileged by the tech economy.
And if Piketty’s is right, we are approaching a reality in which money made from wealth rises faster than wages. So there is a feedback loop in place which only exacerbates the situation.
So some preliminary conclusions: a progressive tax on wealth won’t solve the issue. The education system will require reform, too.
I think this is the central irony of the whole situation: we are working hard to teach machines how to learn. But we are neglecting to improve how people learn.
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.
I’ve read 32 books, which is four short of my goal and also four less than the previous year. It’s still not a bad score though and quality wise the list below contains many gems.
I resolved to read mostly books by women and minority authors. This lead to quite a few surprising experiences which I am certainly grateful for. I think I’ll continue to push myself to seek out such books in the year to come.
There are only a few comics in the list. I sort of fell off the comics bandwagon this year mainly because I just can’t seem to find a good place to discover things to read.
Anyway, here’s the list, with links to my reviews on Goodreads. A * denotes a particular favourite.
