Google UX Designers demystify Artificial Intelligence and Machine Learning

Josh Lovejoy @jdlovejoy, in the first minutes of this video about human-centered machine learning, explains “artificial intelligence is really anything where there is an automated decision being made” and cites, as examples, a toaster and automatic doors. Yes, your toaster is AI! And then “what’s distinct about machine learning as a subset of AI is that decisions are learned”. As simple as that. Refreshening.

You might also want to check the very interesting articles from Google’s People + AI Research team

Gallery of XKCD and other Python matplotlib styles

I’m reading the wonderful “Python Data Science Handbook” by Jake VanderPlas, a book written entirely as Jupyter notebooks! And got excited about matplotlib styles but XKCD “style” was missing so I modified a bit the code for rendering the different styles to include it. Below a small part of the gallery (XKCD style is the first line) which is generated by the jupyter notebook available as a gist on github and embedded below.


I love XKCD graphs, for example the following one, and you can create them with Python!!!

XKCD graph

3 open positions on design thinking available in Trento!

The new adventure I was mentioning few days ago is the Design Research Lab, a joint initiative of University of Trento, Confindustria, Art Institute Artigianelli and Bruno Kessler Foundation.

We are currently recruiting and now there are 3 open positions as research fellow in the Design Research Lab. The duration of the contract is for 12 months. The gross amount is 19.668 euros.
All the details are in the call.
The broad goals of the Design Research Lab (and the tasks of the research fellows) are to effectively promote in public and private organizations the culture of services and their design as levers of product creation and central factors of local development.

The deadline for applying is 12 April 2017 (hurry up!)
Feel free to ask me any question. We might end up working together ;)

Design thinking and how it transformed Airbnb from failing startup to billion-dollar business

Very interesting conversation with Joe Gebbia, co-founder of Airbnb. I share some insights I got by watching the 2013 video.

  • First insight: they were 3 founders in California with a stagnating company (Airbnb), they could have kept staying in their office trying to improve the site, write more software code and instead what did they do? Realising that apartments in New York all had horrible photos, they took a flight (from California to New York!), rented a camera, knock on doors of Airbnb users in New York, took better photos of their apartments and replace them on the site. As Joe says in the interview, “for the first year, we sat behind our computer screens trying to code our way through problems”, instead going to meet their users is one of the pillars of design thinking, its very human-centred focus. Just after this intervention, revenues which were stagnating at 200 dollars per week went up to 400 dollars per week. Near the end, Joe says “if you ever want to understand your product, go stay in the home of your customer” (well, this applies only to Airbnb … and maybe also to Couchsurfing ;)
  • Actually the previous suggestion was given to Airbnb founder by Paul Graham (of Ycombinator, I loved his “hackers and painters” essay!) which suggested it’s okay to do things that don’t scale. What is the meaning? I think it’s again about being very human-centred, going out of the building, develop empathy with specific persons and really understand him/her. So that you can make improvements that really satisfy real needs (of at least one real person!). Scaling to millions of persons will come later, if needed.
  • Another suggestion by Paul Graham was go meet the people which again is the very human-centred side of design thinking. The interviewer asks “what if your company is not for < go out and meet people?> and Joe replies “well, be pirate”, a sort of “do it anyway” but then I asked my self how do you get it accepted? This reminded me of the pragmatic book Undercover User Experience Design.
  • And what can the employee bring back from this “go out and meet people” to the company? Joe replies “visible, tactical, tangible insight that came from somebody is consuming your product or your service”
  • Joe suggests to become the patient (of your service/product). For example, every new employee at Airbnb, during the first week, makes a trip (using Airbnb of course), document it and share insights with his/her new department. Wow!
  • Joe also cites the stars vs heart icons story: when you start as new employee at Airbnb, you ship (a new small feature, something) on day one, so that new employees can experience shipping on day one. A newly hired designer was given the task of looking at the star functionality (an icon you click in order to save a listing you find interesting). After few hours he or she comes back with something like “I think the stars are the kinds of things you see in utility-driven experiences. Instead Airbnb is so aspirational. Why don’t we tap into that? I’m going to change that to a heart.” And Joe “Wow, okay. It’s interesting” and they just shipped the new feature, to the entire userbase (not a/b testing or just shipping it to 10% of the users)! They also added some code in it in order to track it and see how behavior change. And the next day they checked the data and the engagement with the icon increased by over 30%, that simple change from a star to a heart increased engagement by over 30%! In short, let people be pirates, ship stuff and try new things.

Design Thinking: Norman and I (and the stupid question)

I’m starting a new adventure and it is about service design and design thinking, so I thought I could start looking at what Don Norman said about design thinking, right?

In 2010 Norman labelled design thinking as a powerful but false myth with questions such as “Why should we perpetuate such nonsensical, erroneous thinking?” and statements such as “what is being labeled as “design thinking” is what creative people in all disciplines have always done”. Norman argues that designers are not “mystically endowed with greater creativity (…) but they have one virtue that helps them: they are outsiders. People within a group find it difficult to break out of the traditional paradigms, for usually these seem like givens, not to be questioned. Many of these beliefs have been around for so long that they are like air and gravity: taken for granted and never thought about. Outsiders bring a fresh perspective, particularly if they are willing to question everything, especially that which seems obvious to everyone else.”

But in 2013, Norman writes a new post titled “Rethinking Design Thinking” in which he changes a bit his position. The part I like the most is the conclusion where he posits “That is design thinking. Ask the stupid question.” basically arguing that:

What is a stupid question? It is one which questions the obvious. “Duh,” thinks the audience, “this person is clueless.” Well, guess what, the obvious is often not so obvious. Usually it refers to some common belief or practice that has been around for so long that it has not been questioned. Once questioned, people stammer to explain: sometimes they fail. It is by questioning the obvious that we make great progress. This is where breakthroughs come from. We need to question the obvious, to reformulate our beliefs, and to redefine existing solutions, approaches, and beliefs. That is design thinking. Ask the stupid question.

Well, I think I can wonderfully get along with this suggestion, so if you happen to pass by while I’m asking a stupid question (or you are the one I asked the stupid question to), don’t be judgemental, I’m just doing my (new) job ;)

P.S.: I hope you can forgive me for putting so close Don Norman and myself in the title ;)

Which language edition of Wikipedia has more registered women?

A paper of mine published in 2014 started with this simple (but interesting, I think) question ;)
As you might know, Wikipedia is not available only in English but there are almost 300 Wikipedias written in other languages.
So what we did? We computed the percentage of females and males among registered users on 289 language editions of Wikipedia.

The pdf of “Gender Gap In Wikipedia Editing: A Cross-Language Comparison” is available for you to read.
But I suggest you to try to answer to the following questions beforereading the answers (which are in the paper) so that you might play a bit with your stereotypes and prejudices about culture and women around in the world ;)

1) Which language edition of Wikipedia has the largest percentage of registered users setting their gender as female? What is this percentage? It is more or less than 50%?
And 2) what is the language of the Wikipedia with the smallest percentage of women? How close to 0% might this be …?
3) Try to order the following language editions of Wikipedia from the largest percentage of female registered users to the smallest: Arabic, Bulgarian, Catalan, Chinese, French, German, Hindi, Japanese, Korean, Persian, Swedish, Thai. Where does the largest Wikipedia (the English one) is placed?
4) Moreover, considering that setting the gender on Wikipedia is optional and actually few users do it (see details in the paper). Which percentage of users set their gender on English Wikipedia? What is the Wikipedia in which most users set their gender? What is this percentage?

Note that, as written in the paper, of course languages do not map directly to countries. For example, Spanish Wikipedia is heavily edited from Spain but also Latin America and a similar point can be made from Arabic Wikipedia. India has many official languages Hindi, Bengali, Malayalam, Tamil, Marathi but also English. On the other hand, Italian Wikipedia or Catalan Wikipedia are much more “localized”.
Note also that in the paper we arbitrarily decided to consider only editions with at least 20.000 registered users since we computed percentages on registered users (a Wikipedia with 2 users setting their gender would have had percentages of 0%, 50% or 100% clearly not informative) and this filtering step reduced our sample to 76 Wikipedias with a large number of registered users (at least 20.000).
Note also that data refers to March 16, 2013 but we released the Python script as open source so you can re-run it if you are curious about the current situation. You can get the script on Github.

Ok, now you can go to read the paper “Gender Gap In Wikipedia Editing: A Cross-Language Comparison” to get the answers to the previous questions and hopefully be amazed! Enjoy! ;)

Manypedia presented at Wikisym

I uploaded on slideshare the presentation I gave time ago at Wikisym 2012. It is embedded below. There is a comparison of Points of View across different wikis (such as, the Cuban government official wiki, and Conservapedia, Anarchopedia, veganpedia, …) and a comparisons of the same page across different language Wikipedias thanks to Manypedia (such as “List of controversial issues” in English, Chinese and Catalan Wikipedia, “Human rights in the United States” in English and Chinese, “Osama Bin Laden” in English and Arabic, “Vietnam War” in English and Vietnamese, “Northern Cyprus” in Turkish, Greek and English Wikipedia, “Underwear” in English and Arabic)

Manypedia is online at

The paper is at If you like Manypedia and the paper, please cite it. Thanks!

Which Wikipedia pages are edited mainly by females?

Some time ago we developed Wikitrip, a web tool which shows the world location of editors of a chosen Wikipedia page and also the gender of editors, i.e. how many edits were made by males and females. We released Wikitrip as open source on github and we also deployed 3 live APIs: api.php (various stats about a specific Wikipedia page), api_gender.php (returns timestamp and gender for any edit to a specific Wikipedia page by a registered user that specified his/her gender), api_geojson.php (returns a GeoJSON for anonymous edits on a specific Wikipedia page). If you want to use the APIs in your mashups, we’ll be delighted, more details about the APIs can be found at the end of this blog post.

In fact, today I discovered via Gizmodo that Santiago Ortiz has used our Wikipedia Gender API for creating a fantastic visualization of Wikipedia pages based on how many female and male contributors each of the articles has.
Using the cool visualization you can for example “discover” that currently, out of more than 4 million pages in the English Wikipedia, JUST ONE article is edited more by females than males!!! That article, with 7 male editors and 9 male editors, is Cloth menstrual pad.
Note that the API we released is based on data from Wikipedia and that only users who specified their gender in Wikipedia are counted in (these users are a minority, around 10%). Note also that in our Wikitrip visualization we show a plot with number of edits from gendered users while Santiago show the number of different users. For example in Wikitrip you see that the page Cloth menstrual pad has 62 edits from females and 15 edits from males but the different users who edited the page are 7 male and 9 female.

Wikipedia gender divide visualized

Now I give you some more info about the APIs released with WikiTrip so that you can use them as well in your mashups if you wish so.

  1. api.php

    Get various stats about a page


    • article: page title
    • lang: desidered language (default: en)
    • family: wiki family (default: wikipedia)
    • year_count: show edit count per month (default: false)
    • editors: show unique editors for the page (default: false)
    • max_editors: maximum number of editors displayed (only if “editors” option is set)
    • anons: show anonymous unique editors (default: false)
    • top_ten: show top 10% of editors (default: false)
    • top_fifty: top 50 editors (default: false)


  2. api_gender.php

    Get timestamp and gender for any edit by a registered user that specified his gender on a specific page (might be quite slow)


    • article: page title
    • lang: desidered language (default: en)
    • family: wiki family (default: wikipedia)


  3. api_geojson.php

    Get a GeoJSON for anonymous edits on a specific page


    • article: page title
    • lang: desidered language (default: en)
    • family: wiki family (default: wikipedia)


P.s.: the coder of all Wikitrip awesomeness is the amazing Federico “fox” Scrinzi!

Models of economic production, Encarta vs Wikipedia, and sober economists

An excerpt from Dan Pink’s TED talk “The surprising science of motivation

The mid-1990s, Microsoft started an encyclopedia called Encarta. They had deployed all the right incentives, all the right incentives. They paid professionals to write and edit thousands of articles. Well-compensated managers oversaw the whole thing to make sure it came in on budget and on time. A few years later another encyclopedia got started. Different model, right? Do it for fun. No one gets paid a cent, or a Euro or a Yen. Do it because you like to do it.

Now if you had, just 10 years ago, if you had gone to an economist, anywhere, and said, “Hey, I’ve got these two different models for creating an encyclopedia. If they went head to head, who would win?” 10 years ago you could not have found a single sober economist anywhere on planet Earth who would have predicted the Wikipedia model.

MIT Press book “The Reputation Society” (containing a chapter by me) is out!

The MIT Press I contributed to with a chapter is out! It is titled “The Reputation Society: how online opinions are reshaping the offline world” and edited by Hassan Masum and Mark Tovey.
It is available on MIT press and on Amazon.
The chapter I wrote is titled Trust It Forward: Tyranny of the Majority or Echo Chambers? and on it I ramble about objectivity/subjectivity, minorities/majorities, etc.

If reputation systems weight all perspectives similarly, they may devolve into simple majority rule. But if they give each user reputation scores that take only other similar users’ opinions into account, they run the risk of becoming “echo chambers” in which like-minded people reinforce each others’ views without being open to outside perspectives. Massa discusses design choices and trust metrics that may help balance these two extremes and the broader implication for our future societies.

the reputation society book cover The book received endorsements by people I really admire.
“As our societies expand from local villages to global networks, our ways of assessing and sharing reputation—the foundation of trust and community—must also evolve, but how? The thoughtful and thought-provoking essays in The Reputation Society bring a wide range of perspectives to this question, including the design of technological solutions, applications in philanthropy, science and governance, and warnings about the loss of privacy and autonomy. It is a fascinating collection of readings not only for scholars, but for anyone interested in the dynamics of the reviews and recommendations that shape our decisions—or in the future of how we will judge and be judged.”
Judith Donath, Fellow, Berkman Center for Internet and Society, Harvard University

“Today is tomorrow’s yesterday. These provocative essays, by some of the leading thinkers in the domain of reputation systems, illuminate how reputations regulate actions across time and social distance and point to the opportunities and obstacles that reputation systems present for commerce and democracy.”
Paul Resnick, Professor, University of Michigan School of Information

“The Reputation Society enriches the discussion of reputation by bringing together technologists, philosophers, legal scholars, and industry leaders to sort through the promise and perils we face today. It covers the practical, for those interested in the nuts and bolts of the challenges we face today, and the theoretical, for those looking to engage in broader discussions of the ethical and moral concerns. In short, a terrific and enlightening read!”
Danielle Keats Citron, Professor of Law, University of Maryland School of Law

The list of my co-authors is also very delightful.
Trust, reputation systems, and the immune system of democracy / Craig Newmark
Building the reputation society / Hassan Masum, Mark Tovey, & Yi-Cheng Zhang
Designing reputation systems for the social web / Chrysanthos Dellarocas
Web reputation systems and the real world / Randy Farmer
An inquiry into effective reputation and rating systems / John Henry Clippinger
The biology of reputation / John Whitfield
Regulating reputation / Eric Goldman
Less regulation, more reputation / Lior Strahilevitz
The role of reputation systems in managing online communities / Cliff Lampe
Attention philanthropy : giving reputation a boost / Alex Steffen
Making use of reputation systems in philanthropy / Marc Maxson & Mari Kuraishi
The measurement and mismeasurement of science / Michael Nielsen
Usage-based reputation metrics in science / Victor Henning, Jason Hoyt, and Jan Reichelt
Open access and academic reputation / John Willinsky
Reputation-based governance and making states “legible” to their citizens / Lucio Picci
Trust it forward : tyranny of the majority or echo chambers? / Paolo Massa
Rating in large-scale argumentation systems / Luca Iandoli, Josh Introne, & Mark Klein
Privacy, context, and oversharing : reputational challenges in a Web 2.0 world / Michael Zimmer & Anthony Hoffman
The future of reputation networks / Jamais Cascio
“I hope you know this is going on your permanent record” / Madeline Ashby & Cory Doctorow.

The cover of the book reads as follows.

In making decisions, we often seek advice. Online, we check Amazon recommendations, eBay vendors’ histories, TripAdvisor ratings, and even our elected representatives’ voting records. These online reputation systems serve as filters for information overload. In this book, experts discuss the benefits and risks of such online tools.

The contributors offer expert perspectives that range from philanthropy and open access to science and law, addressing reputation systems in theory and practice. Properly designed reputation systems, they argue, have the potential to create a “reputation society,” reshaping society for the better by promoting accountability through the mediated judgments of billions of people. Effective design can also steer systems away from the pitfalls of online opinion sharing by motivating truth-telling, protecting personal privacy, and discouraging digital vigilantism.