Tag Archives: technology

Artificial Intelligence: how many AI principles or ethics guidelines are there and what do they say?

This is it: the study I had been working on all winter (together with my colleague Marcello and our professor Effy Vayena) was published in Nature Machine Intelligence. It is an in-depth review of a corpus of 84 documents consisting of (or containing) ethical principles for artificial intelligence. Although no single principles occurred in all documents, some are more prevalent than others — and others are strikingly underrepresented.

Here is a link to the article “The global landscape of AI ethics guidelines”: https://www.nature.com/articles/s42256-019-0088-2. Unfortunately it is behind a paywall (and we were not able to select the option of having the article published Open Access), but if you get in touch via e-mail (anna.jobin at sociostrategy), on Social Media, or via ResearchGate, I will be more than happy to send you the article. (*)

This is what the abstract says:

In the past five years, private companies, research institutions and public sector organizations have issued principles and guidelines for ethical artificial intelligence (AI). However, despite an apparent agreement that AI should be ‘ethical’, there is debate about both what constitutes ‘ethical AI’ and which ethical requirements, technical standards and best practices are needed for its realization. To investigate whether a global agreement on these questions is emerging, we mapped and analysed the current corpus of principles and guidelines on ethical AI. Our results reveal a global convergence emerging around five ethical principles (transparency, justice and fairness, non-maleficence, responsibility and privacy), with substantive divergence in relation to how these principles are interpreted, why they are deemed important, what issue, domain or actors they pertain to, and how they should be implemented. Our findings highlight the importance of integrating guideline-development efforts with substantive ethical analysis and adequate implementation strategies.

On twitter I have given a little more information about our findings in a short thread:

There are more tweets, and if you click on the date link you should be able to acces the whole thread.

Although we analyzed 84 documents, many more AI principles and ethics guidelines exist today. For one, there is the time difference between the time one submits the first version of an article to a journal and the moment it is published (peer-review and production take time, and I would like to add that NMI has been much faster than I, a qualitative social scientist, have been used to from other experiences). But there is also another catch-22, due to our research design: our in-depth analysis takes time, and while we were analyzing new guidelines, even more principles would be issued during that time. At one point we simply had to wrap up… This will also explain why our analysis only takes into account the version of the documents our methodology provided us with, and does not account for subsequent versions (the Montreal Declaration, for example, was in stakeholder consultation stage so our analysis is not about its final version).

Therefore, and for methodological reasons, we are only able to provide a snapshot in time. Yet we hope that our research can serve as an overview and a stepping stone for anyone involved with “ethical AI”, from researchers and scholars to technology developers to policy makers.

(*) FWIW we did post a pre-print version on arXiv.org, though I am compelled to highlight that the arXiv version is not identical with the NMI journal version: it is our author version, before peer-review, and in addition to the clarifying modifications we were able to make in the final version thanks to the reviewer comments, one document was initially wrongly attributed to the UK instead of the USA (something we were able to correct thanks to a generous reader comment).

Digitalkompetenzen im Kontext (uvm)

Am 8. Mai 2019 durfte ich auf Einladung der EMEK/COFEM (der eidgenössischen Medienkommission, resp. der commission fédérale des médias) zusammen mit Friederike Tilemann den ersten Drittel eines überaus spannenden Nachmittagsprogramms zum Thema “Streamingdienste und Plattformen: Herausforderungen für Medien & Öffentlichkeit” bestreiten. Wir thematisierten Medien- und Digitalkompetenzen, danach sprachen Judith Möller und Sébastien Noir über die Relevanz von Algorithmen, und zuletzt widmeten sich Natascha Just und Wolfgang Schulz dem Thema Gouvernanz. Der Anlass war öffentlich und gut besucht. Im Folgenden nun ein subjektiver Allerkürzestbericht meinerseits, einschliesslich einer — wie ich doch hoffe — lesefreundlichen Version meiner Eingangspräsentation. Denn, wie heisst es so schön: sharing is caring.

Nach den Grussworten des EMEK/COFEM-Präsidenten Otfried Jarren stellte Manuel Puppis den derzeitigen Stand des Arbeitspapiers der Kommission vor. Die Erkenntnisse des Tages sollen in die bevorstehende neue Version des Dokuments einfliessen. Dies habe, zusammen mit dem Wille zur Förderung des öffentlichen Dialogs, den heutigen Anlass motiviert. Danach teilte Friederike Tilemann ihr Expertenwissen über Medienkompetenzen: gerade Heranwachsende brauchen sowohl Kompetenzen als auch Schutz, um gewinnbringend mit Medien umgehen zu können. Und erstere beinhalten nicht nur Nutzung, sondern auch Wissen, Kritikvermögen, reflektiertes Handeln und Gestaltungsfähigkeit.

Dadurch wurde mir natürlich ganz komfortabel ein Ball zugespielt, den ich nun ins Feld der Digitalisierung bringen konnte. Denn das meiste, was bisher zu Medienkompetenzen gesagt worden ist, bleibt wichtig und relevant. [Das ist übrigens auch aus Genners “Kompetenzen und Grundwerte im digitalen Zeitalter” ersichtlich.] Ich biete keinen Widerspruch sondern Ergänzung an.

Meine Präsentation ging ebenfalls auf die Frage ein, wie mit digitalen Medien umgegangen werden kann, aber aus einer etwas andern Perspektive. Mein Hintergrund ist einerseits in Soziologie, Volkswirtschaft und Wirtschaftsinformatik, andererseits bringe ich durch meine Vergangenheit als selbständige Social Media Beraterin auch praktische Erfahrungen mit. Untenstehend nun meine Folien — die ich, um der Mehrsprachigkeit der Schweiz an diesem gesamtschweizerischen Anlass wenigstens halbwegs gerecht zu werden, auf französisch verfasst hatte — sowie ein ungefähres Transkript meiner 10minütigen Präsentation, angereichert mit Klammerbemerkungen und ein paar Links. Continue reading

Technology, innovation and society: five myths debunked

Recently, I held a lecture about the digital transformation for the franco-swiss CAS/EMBA program in e-tourism. The tourism industry not being my specialty, and the “social media” aspects having been thoroughly covered by colleagues,Media Technology old and new I had been specifically asked to convey a big picture view.

I chose to address some overall issues related to ICT (information & communication technology), innovation and society by debunking the following five myths:

  1. Ignoring the digital transformation is possible
  2. Technological progress is linear
  3. Connectivity is a given
  4. Virtual vs. “real” life
  5. Big Data – the answer to all our questions

Each of these points would deserve an treatise on its own, and I will not be able to go into much details in the scope of this article. I nevertheless wanted to share some of the links and references mentioned during my lecture and related to these issues. If you prefer reading the whole thing in French, please go to Enjeux technologiques et sociaux: cinq idées reçues à propos du numérique, which is the corresponding (but not literally translated) article in French.

Myth no. 1: Ignoring the digital transformation is possible

While discussions of online social networks have become mainstream, the digital transformation goes way beyond social media. It is about more than visible communication. It is about automation, computation, and algorithms. And as I have written before: algorithms are more than a technological issue because they involve not only automated data analysis, but also decision-making. In 1961 already, C.P. Snow said:

«Those who don’t understand algorithms, can’t understand how the decisions are made.»

In order to illustrate the vastness of computation and algorithmic automation I mentioned Frédéric Kaplan’s information mushroom (“champignon informationnel”), my explorations of Google Autocomplete, as well as the susceptibility of a job to be made redundant in the near future by machine learning and mobile robotics (cf. this scientific working paper, or the interactive visualisation derived from it).

Myth no. 2: Technological progress is linear

This point included a little history including sociology of knowledge and innovation studies.

Continue reading

[French] Enjeux technologiques et sociaux: 5 idées reçues à propos du numérique

Exceptionally, this article is in French. English speaking readers might want to head over to Technology, innovation and society: five myths debunked.

Cet article esquisse mon intervention dans un module de formation EMBA / CAS il y a quelques jours. Le but était de sensibiliser les participants aux enjeux des technologies de l’information comme sources d’innovations majeures et de les rendre attentifs à quelques enjeux sociaux des TIC. Afin qu’un tour d’horizon aussi vaste soit un tant soit peu digeste, j’ai décidé de le présenter en cinq chapitres qui démontent certaines idées reçues à propos du numérique:

  1. Il est possible d’ignorer le numérique
  2. Le progrès technologique est linéaire
  3. La connectivité est un acquis
  4. Il y a le virtuel et il y a la “vraie vie”
  5. Les “big data”: la solution à tout

En voici ci-dessous la présentation, et ensuite quelques phrases explicatives avec liens/références.

La présentation:

Idée reçue no. 1: Il est possible d’ignorer le numérique

Le domaine du numérique est souvent considéré uniquement dans une perspective communication/marketing, une perspective parfois réduite aux seuls sujets des sites web et des réseaux sociaux en ligne. Et alors qu’il est possible pour une entreprise notamment de se passer d’une page facebook en toute cohérence avec sa stratégie, il n’en est pas de même avec la dynamique et l’évolution numérique au sens large. Ce parce que la révolution numérique ne concerne de loin pas que les “social media”. Elle comprend toute sorte d’automatisation algorithmique. Une citation parlante à ce sujet a été dit par C.P. Snow en 1961 déjà et je l’avais reprise dans un billet précédent (en anglais) il y a deux ans et demi:

«Those who don’t understand algorithms, can’t understand how the decisions are made.»

Illustrant quelques enjeux d’automatisation algorithmique, j’ai mentionné le “champignon informationnel” de Frédéric Kaplan, mes explorations de Google Autocomplete, et les calculs de la “probabilité de remplaçabilité” d’un emploi (provenant d’un working paper scientifique, transformés en visualisation interactive) grâce aux avancées dans les domaines du machine learning et de la robotique mobile.

Idée reçue no. 2: Le progrès technologique est linéaire

Pour ce point, une petite plongée dans la sociologie de la connaissance et de la technologie:

Continue reading