Keynote at MODELS2022 – ResponSE

Responsible Software Engineering and ‘Social Good’

by: Maria Angela Ferrario, Queen’s University Belfast, U.K.

Over the last decade, the software engineering community has emerged as one particularly fertile ground for both asking deep societal questions (“what is social good”?) and developing responsible software engineering practices in answer to such questions. In this talk, I will first, use examples drawn from my own research to illustrate the transformative force of opening up SE research and practice to wider constituencies, and in particular the hard to reach and vulnerable communities; I will then highlight key challenges and good practices being adopted by software industry and research to anticipate, mitigate, and reflect on the intended and unintended consequences of the technologies that we bring to life.

Venue: ACM / IEEE 25th International Conference on Model Driven Engineering Languages and Systems (MODELS)

Seminar @ LERO/OU – Human Values in SE


The study of human values in software engineering (SE) is increasingly recognised as a fundamental human-centric issue of SE decision making processes. However, values studies in SE still face several issues, including the difficulty of eliciting values in a systematic and replicable way, the challenges of measuring and monitoring values over time, and a limited practice-based understanding of values among software practitioners (and in general). This talk outlines our approach and the work done so far to address these issues, and to advance the study of values in SE and its use into practice.

Slidedeck (LowRes)

Interactive Values Q-Sort (via Miro Board – view only: collective arrangement display


ViC at Not-Equal Summer School

Not Equal Logo

ViC was excited to join the first Not-Equal summer school,  which took place in Swansea from the 27-30th August 2019 and explored the intersections between Algorithmic Social Justice and Digital Security through a programme of talks, workshops and panel sessions. ViC hosted a session on ‘Values-First and Responsible Computing‘, abstract below:


The software industry, computing research, and wider society have yet to fully grasp the potentially devastating consequences of unleashing, at scale, software that has been built without putting societal concerns and people’s lives first. This is even more critical with the emergence of new trends, especially with AI, where software is already making autonomous decisions, e.g. in the financial sector. Following an increasing number of high-profile software scandals and malpractices (e.g. the VW deceit software, FB/Cambridge Analytica illicit personal data harvesting, and Boeing 373 Max anti-stall software disasters), calls have been made for radical changes in business models and tough policies to strongly regulate against pervasive software industry malpractices. Although much needed, laws and regulations can be broken or circumvented. What cannot be so easily broken is a values-informed, diverse, and well-connected community of computing practice; one that understands what human values are, what social responsibility means, and the way that values and responsibility are written into code.  This talk will share research approaches, tools, findings, and future directions from on-going work at Lancaster University.

ViC at Dagstuhl

ViC was at Dagstuhl!

ViC at Dagstuhl
ViC at Dagstuhl
Title / Seminar number: 19291

Values in Computing


Christoph Becker (University of Toronto, CA)
Gregor Engels (Universität Paderborn, DE)
Andrew Feenberg (Simon Fraser University – Burnaby, CA)
Maria Angela Ferrario (Lancaster University, UK)
Geraldine Fitzpatrick (TU Wien, AT)

Aim: to examine the  relations between human values, computing technologies and society. It does so by bringing together practitioners and researchers from several areas within and beyond computer science, including human computer interaction, software engineering, computer ethics, moral philosophy, philosophy of technology, investigative data science, and critical data studies.

Outcomes: a research agenda to be included in the Dagstuhl Report; and a jointly designed ‘Values in Computing’ teaching module, to be piloted across a selection of participating universities.

Values in Computing Dagstuhl micro site

Dagstuhl seminars are a fantastic opportunity for academics and practitioners  to come together, exchange experiences, explore ideas and put research to work. The seminar took pace on 15-19 July 2019.


Measuring Human Values in Software Production

When & Where

Data Science, Machine Learning and Artificial Intelligence, SIAM-IMA  Early Career Researcher Conference, LIverpool, 3-5 April 2019


Human values, such as prestige, social justice, and financial success, influence software production decision-making processes. While their subjectivity makes some values difficult to measure, their impact on software -and of software on society -motivates my research. This talk makes the case for the study of human values in software production and offers two key principles in order to advance this research agenda. Firstly, the significance of values as distinguished from, though connected to, ethics; and secondly, the need for clear theoretical to values study. It then introduces a selection of tools and techniques that have been designed in accordance with these two principles and used with computing professionals from research, education, and industry. It concludes with discussion around lessons learnt, ongoing challenges, and future directions.

Delivered By MAF @ViC

AI & Human Values – Workshop

Where and When

C121 Collaborative Learning Space, Building C, Monash Caulfield Campus
Thursday 24 January 2019 2-4pm


With the rapid advances of AI, concerns around the undesirable and unpredictable impact that AI may have on society are mounting. In response to such concerns, leading AI thinkers and practitioners have started drafting principles and guidelines to envision an AI that would benefit humanity instead of causing harm. Underpinning these principles is the perceived importance for AI to be aligned to human values and promote the ‘common good’. We argue that efforts from leading AI thinkers and practitioners must be supported by constructive critique, dialogue and informed scrutiny from different constituencies asking questions such as: what and whose values? What does ‘common good’ mean, and to whom?

The aim of this workshop is to take a deep dive into human values, examine how they work, and what structures they may exhibit. Specifically, our twofold objective is to capture the diversity of meanings for each value and their interrelationships in the context of AI. We will do so by using some of the tools and techniques developed as part of the Values in Computing (ViC) research.


Workshop structure and high-level outcomes available on request (send MAF  an email ).

Tool Used:

AI Values Q-SortAI Values Q-Sort, a V-QS adaptation

Alien AI & the Criterion of Intelligence

Workshop @ PACTMAN: Trust, Privacy and Consent in Future Pervasive Environments Symposium 10-11 December 2018. Event Page.

Alien AI – Mission Sheet

“An Alien Intelligence has been discovered. As it happens, it is an Artificial form of Alien Intelligence emerged as a colony of spawn-like creatures. It is commonly accepted that entities exhibiting Artificial Intelligent (AI) characteristics can be described as intelligent agents, that is systems that perceive and act in some environment. However, being an Alien form of AI, the exact criterion for intelligence is difficult to establish and the environment of origin unknown. Our goal is to explore and specify this very criterion of intelligence and, from that, explore the potential attitudes and behavior of Alien AI in a range of environments.”

This workshop is part of the Values in Computing (ViC) research programm and facilitated by Marie & Steve from Team ViC. ViC receives support from the EPSRC.

AI & Human Values – Workshop @CIRN, Italy

AI hatchlings
AI hatchlings in 3DP production. Photo by sf@vic

The ViC team has been invited to deliver a workshop on Human Values & AI  at CIRN, Prato, Italy, October 2018.

This workshop  takes a deep dive into human values, examines how they work, and what structures they may exhibit. It uses some of the new tools developed for the AI & Ethics seminar series just held at Alpbach and covers some of the questions explored in our previous post on AI & Ethics.

Full Workshop Proposal


AI has seen a massive and rapid development in the past twenty years. With such accelerating advances, concerns around the undesirable and unpredictable impact that AI may have on society are mounting. In response to such concerns, leading AI thinkers and practitioners have drafted a set of principles – the Asilomar AI Principles – for Beneficial AI, one that would benefit humanity instead of causing it harm.

Continue reading “AI & Human Values – Workshop @CIRN, Italy”

AI & the Media

This post was drafted  in response to journalists’ questions  (e.g. from Wiener Zeitung  and Forbes)  in occasion of a week-long AI & Ethics  seminar and of the  ‘State of AI’ panel discussion i was invited to. Shame they asked me before James Mickens gave his phenomenal Usenix2018 keynote on ML, IoT et al. . I would have simply directed them to it.

  • Q1: In addition to a Universal Declaration of Human Rights, do you need a Universal Declaration of cyborg / robot rights?
  • Q2: Who has to be protected from whom?
  • Q3: What importance do programmers have in the future?
  • Q4: How can one ensure that there is a universal catalog of ethical behavior in artificial intelligence?
  • Q5: Do man and machine merge?
  • Q6. What are the future challenges in coping with artificial intelligence and transhumanism?
  • Q7: Have we arrived in the first phase of transhumanism?
  • Q8: is it time that, alongside the IT industry, more and more humanities scientists are involved in the questions of the technological future?

Original list of questions


First, let’s clarify what we mean by Artificial Intelligence. AI is an umbreall terms for a number of related technologies and field of studies.  Suchman‘s description of AI is a good starting point:  “AI is the field of study devoted to developing computational technologies that automate aspects of human activity conventionally understood to require intelligence”. The words ‘conventionally understood’  are key.

In the last 20 years, this field of study has been focused on the “construction of intelligent agents — systems that perceive and act in some environment. In this context, the criterion for intelligence is related to statistical and economic notions of rationality —  the ability to make good decisions, plans, or inferences” (AI open letter  2015).

The combination of access to big data, increasing computing process power, and market promises has vastly accelerated AI development in the last two decades. The  ‘criterion for intelligence’  is here linked to rational thinking as defined by statistics and economics – e.g. in terms of utility, and performance.

This means that, once humans have designed the problem space in which machine intelligence operates, this will act rationally. Rationally does not necessarily mean fairly and considerately.


To better answer the   questions,  I have made the distinction  between ‘Intelligent agents type A and ‘Intelligent agents type B, this distinction is fictional, and broadly overlaps with the distinction between ‘narrow’ and ‘general AI’ .  Put it simply,  it focuses  on what is available now and what we do not have yet, but may have in the future.

  1. Intelligent agents A – this is what  we have now, systems that use AI computational techniques (e.g.  machine learning) for a variety of tasks with some specific goal (e.g. speech recognition, image classification, machine translation). These component tasks can be used in isolation or combined. Examples include image recognition for cancer detection, and data models for diabetes prediction.
  2. Intelligent agents B – this is what we do not have yet, but it is a the centre of much media attention: an engineered non-biological sentient entity  (i.e. synthetic, hybrid) equipped with General AI  unbounded capabilities. In other words, an entity engineered to successfully perform – and surpass – any human intellectual task.

I would not say that is not possible to build a ‘type B’ intelligence, but I’d question the values underpinning such desire.


The journalists’ questions were many and complex. I thought it best to reason about them with ‘team ViC’. Below are my personal reflections, informed by team discussions. As an experiment, each of us also gave “one-word” answer to each of your questions. I have summarized them at the start in italic.

Q1: In addition to a Universal Declaration of Human Rights, do you need a Universal Declaration of cyborg / robot rights?

No. (not until)

Given our Human Rights track record, we should not build  ‘type B’ machines that need to be granted rights until the rights of every single human being is respected. Also granting an ‘electronic person’ status to a machine, may be just another way for lifting tech industry from their responsibilities.

The Universal Declaration of Human Rights (UDRH) is a testament to both human ‘kindness’ and to our struggle to honor our very own rights.  We, as human species, are currently in breach of every single UDRH article. Furthermore, old problems not only seems to stay, but they seem to morph  and grow in scale, for example:

  • Slavery  is rife and on the rise. There is  now an estimate 40M people in slavery (vs 30M in 2013). Slavery has morphed into more subtle, hidden and deeply pervasive new  forms.
  • Wars still ravage many of our nations, and the trend is upwards. AI development and the military are  historically  intertwined and problematically so (e.g.  the 4000 Google employees project Maven walk out).
  •  Inequalities both  social and economic are widening and it is happening at our door step.  Research has found that 1 in 3 children in Britain lives in poverty and that this is a raising trend.

How can we be capable of respecting entities that are not ‘us’ when we are not good at respecting our own rights? Or, in reverse, are we sure that we can build machines that will respect humans? Some may dream up of Sophia, but it is Mary Shelley who seems to be currently stealing the  show.

Many top AI researchers argue that we should not grant machines the status of an electronic person – to make machines responsible of their actions (good or bad) would mean that their designers and manufacturers could be lifted from their responsibilities. What would you do if a machine does something wrong? Fine it? Put it into jail?

Q2: Who has to be protected from whom?

Humans from Humans

(See Q1 above)

Q3: What importance do programmers have in the future?

Much and Hardly Any

Perhaps too much focus is placed on  individual developers’ responsibilities, whereas these responsibilities are often distributed.  More emphasis should be placed, firstly, on the importance of investigating the changes that computational-intensive technologies are bringing to society, starting by reflecting on our own individual lives. Secondly, on questioning whether these changes are desirable or not, and, most importantly, desirable to whom. Desirability is a difficult nut to crack, Russel et al. try to explain why.

Q4: How can one ensure that there is a universal catalog of ethical behavior in artificial intelligence?

One Can Not

Philosophically, this assumes the possibility (and desirability?) of Universal Ethics to be used by machines.  Ethics are codified principles of what a society, organisation, or any other human constituency considers right or wrong;  behaviour is situated, contextual, and salient. Formalised Universal Ethics  do not guarantee ethical behaviour because it is context-dependent, particular,  and volatile.

Technically, we can improve the transparency and externalization of machine reasoning. For example,  research in  autonomous systems  is looking into externalizing the reasoning underpinning their behavior, in this paper, they describe their technical challenges.

Q5: Do man and machine merge?


Man and machine have long merged, the biggest merge is with the Internet, to which we are constantly and collectively connected. Individually, we also have pace makers, defibrillators, insulin pumps – complexity and scale will increase, but fundamentally the merge has already happened. Cybernetics, is about technology-driven  systems  control.  I have seen ‘dying’  ravaged by a simple pacemaker,  what could the implications be – for both the living and dying – of intelligence augmentation ?

Q6. What are the future challenges in coping with artificial intelligence and transhumanism?

Batteries, jobs, children.

Firstly, the intelligent machines of which we speak, need power,  energy, ‘food’. How will they be fed? Who will feed them? Bio-fuel crops already compete with human foodstuff production, and predictions indicate that communication industry is to consume more than 20% of world electricity by 2020.

Secondly, much focus is placed on human / machine competitiveness in the job market.  I’d also keep a closer eye on the roles that humans have and should have in society,  how those may get eroded (e.g. the joy and opportunities to exercise creativity and problem solving, care for children, care for the elderly).

These are roles that, I’d argue, define the very essence of being human. Is trans-humanism really what most of us want for our children? Is that what our older selves want?

Q7: Have we arrived in the first phase of transhumanism?


There is certainly an increased desire for trans-humanism, and where there is a will, there is a way. Human history has been shaped by the desire and reverence for ‘entities’ that transcend us. When such entities cannot be found, we imagine, evoke, and, eventually build them.

Q8: is it time that, alongside the IT industry, more and more humanities scientists are involved in the questions of the technological future?

Maybe too late

Humanities have been for long involved in these questions. Historians and philosophers have been working on pattern recognition for centuries, and noted that at times it works and other times it doesn’t.

  1. In addition to a Universal Declaration of Human Rights, do you need a Universal Declaration of cyborg / robot rights?
  2. Who has to be protected from whom?
  3. What importance do programmers have in the future?
  4. How can one ensure that there is a universal catalog of ethical behavior in artificial intelligence?
  5. Is not it easier to teach artificial intelligence an ethical framework along which decisions are made?
  6. Do man and machine merge?
  7. Which social, ethical, cultural and political consequences arise from this?
  8. Are there technical or biological. Limits of the merger, where are they going so far?
  9. Why do not you talk about cyborgs anymore?
  10. How human has AI to be? Is human society ready for AI?
  11. What are the future challenges in coping with artificial intelligence and transhumanism?
  12. Have we arrived in the first phase of transhumanism?
  13. Is it time that, alongside the IT industry, more and more humanities scientists are involved in the questions of
    the technological future?

“Fear sells, and articles using out-of-context quotes to proclaim imminent doom can generate more clicks than nuanced and balanced ones.” {AI Q&As}. Media should support mature and informed conversations on this topic. This blog post has been drafted as  a basis for conversation with the media.

(MY) research context

I work at the intersection of human computer interaction (HCI)  and  software engineering (SE).  My research focuses on human values in computing, particularly values in software production, but not specifically in AI.

My expertise is in applied digital innovation (i.e.  in health, environmentsocial change). I  examine the role and impact of digital innovation on society (and vice-versa), often through rapidly prototyped technologies.  I have also put some narrative about my background below to furthercontextualize my answers.


I did Philosophy and Social Psychology as my first degree/masters in Italy (Universita’ Cattolica, Milano). Two weeks after my Viva,  I left Italy for Ireland to learn English. I only planned to stay for three months. A year after I  was awarded a  place on a MSc in Multimedia Systems Design, at the Engineering Department of Trinity College Dublin, Ireland; after that I was offered the PhD at the Computer Science Department, University College, Dublin.

My PhD was in a branch of AI (Case Based Reasoning); it was 15 years ago. Immediately after my PhD I left academia and the field precisely because I felt uncomfortable with the research domain and its applications (i. e. user profiling for commercial purposes). After that, I worked as a project manager for a  EU agency. The focus was on peace building and reconciliation through technology and economy development of EU crossborder regions.

Fast forward several year, and I am back in academia as a lecturer in computer science. Underpinning my research,  is a passion for understanding  the interplay between human values and computing. This comes from years of working on digital innovation research partnerships with vulnerable parts of our  society.