Computing and Society

Computing
Ethics
Technology and Society
Responsible Innovation
Human-Centered Design
A critical and applied reflection on the transformative role of technology in the contemporary world, integrating ethics, social values, and human impact into the software development lifecycle.
Author

Marcos M. Raimundo

Published

September 18, 2026

PDD

This course proposes a critical and applied reflection on the transformative role of technology in the contemporary world. Far from being a purely technical or neutral activity, computing is approached as a deeply human and social practice whose architectural choices, algorithms, and business models directly impact people’s lives, democracy, the environment, and labor relations.

Final Objectives

The primary goal of the course is to enable future computing professionals and researchers to expand their analytical and ethical repertory. By offering concepts, methodologies, and tools to anticipate moral conflicts, identify algorithmic biases, and integrate social values into the software development lifecycle, students transition from philosophical and normative foundations to practical methodologies for responsible innovation and ethical design.

Course Content

Click on each lesson to access its detailed planning and study materials.

Part 1: Foundations of Computing and Ethics

  • Lesson 1: Computing as a Socio-Technical System
    • Objectives: Understand that computing is not composed solely of technical elements (hardware and software), but constitutes a socio-technical system where technology, human beings, organizations, and culture mutually influence each other.
    • Expected Competencies: Ability to analyze computing artifacts within their broader social, cultural, and organizational contexts, identifying non-technical feedback loops and systemic impacts.
    • Recommended Reading:
      • Van de Poel & Royakkers (2011) – Chapter 1: The Responsibilities of Engineers (esp. §1.6, “The Social Context of Technological Development”).
      • Maciel & Viterbo (2020) – Vol. 2, Capítulo 10: Cultura na Prática da Computação — correção: a referência original (“Vol. 2, Capítulo 2: Análise Cultural de Sistemas Computacionais”) não existe no livro; o Vol. 2 não tem Capítulo 2 (a numeração começa no Cap. 9), e o Capítulo 2 do Vol. 1 é sobre pós-graduação, sem relação com o tema. Substituído pelo capítulo real mais próximo tematicamente.
      • Steen (2022) – Chapter 3: Is Technology a Neutral Tool? — leitura complementar adicionada nesta sessão; cobre exatamente a tese da não-neutralidade e da coformação mútua entre pessoas e tecnologia.
    • Date and Speaker: TBD | Marcos M. Raimundo
  • Lesson 2: What is Ethics, and The Ethical Cycle
    • Objectives: Introduce the main branches of normative ethics (consequentialism, deontology, and virtue ethics) and train students in using the “Ethical Cycle” as a methodological tool to analyze and resolve moral dilemmas in IT.
    • Expected Competencies: Ability to apply ethical frameworks systematically to resolve complex technology-related moral dilemmas using structured deliberation steps.
    • Recommended Reading:
      • Van de Poel & Royakkers (2011) – Chapter 3: Normative Ethics & Chapter 5: The Ethical Cycle — correção: a ementa original dizia “Chapter 4: The Ethical Cycle”; pelo sumário real, o Cap. 4 é “Normative Argumentation” e o Ciclo Ético é o Cap. 5 (p. 133).
      • Marc Steen (2022) – Chapter 16: Methods to ‘do ethics’ in your project — correção: a ementa original dizia “Chapter 6: Ethical Reflection, Inquiry, and Deliberation”, título que não existe no livro (o Cap. 6 real é “Privacy is about more than ‘privacy’”; a frase citada é o tema recorrente do livro, introduzido no Cap. 2 e detalhado no Cap. 16).
    • Date and Speaker: TBD | Marcos M. Raimundo
  • Lesson 3: Computing, Its Domains, and Professional Responsibility
    • Objectives: Map the field of computing, discuss the relevance and application of professional codes of ethics (ACM, SBC, IEEE), and examine the scope of active and passive professional responsibilities toward society.
    • Expected Competencies: Ability to align technical practices with established professional codes of ethics and evaluate individual liability in software failure or societal harm scenarios.
    • Recommended Reading:
      • Maciel & Viterbo (2020) – Vol. 1, Capítulo 1: A Formação em Computação, Capítulo 5: Regulamentação da Profissão, & Capítulo 7: Ética Profissional em Computação — correção: a ementa original citava títulos que não existem no livro (“Panorama do Ensino Superior em Computação no Brasil” para o Cap. 1; “O Exercício da Profissão em Computação e os Aspectos Regulatórios no Brasil” para o Cap. 5); corrigidos para os títulos reais, e adicionado o Cap. 7, que cobre diretamente ética profissional em computação — antes ausente da leitura recomendada.
      • Van de Poel & Royakkers (2011) – Chapter 2: Codes of Conduct.
    • Date and Speaker: TBD | TBA

Part 2: Computing and Its Impacts

  • Lesson 4: Human, Social, and Ethical Dimensions of Software Engineering
    • Objectives: Explore software engineering as a sociotechnical discipline, analyzing industry roles, communication dynamics (Conway’s Law), and requirements elicitation as social processes. Demonstrate how to translate social responsibilities and human impact into architectural decisions, requirements, and development workflows.
    • Expected Competencies: Ability to map stakeholder interactions and industry roles, analyze sociotechnical trade-offs in requirements engineering, and translate ethical commitments into non-functional requirements and concrete code architecture.
    • Recommended Reading:
      • Ian Sommerville (2015) – Software Engineering (10th Ed.), Chapter 1 (Introduction to Sociotechnical Systems) and Chapter 4 (Requirements Engineering).
      • Catherine D’Ignazio & Lauren F. Klein (2020) – Data Feminism, Chapter 2: “Collect, Analyze, Imagine, Teach” (Socio-technical Power Structures in Data Systems).
      • Marc Steen (2022) – Ethics for People Who Work in Tech, Chapter 5: Value Sensitive Design and Responsible Innovation.
      • Mel Conway (1968) – How Do Committees Invent? (Conway’s Law foundational paper on team communication and architecture).
    • Date and Speaker: TBD | TBA
  • Lesson 5: Understanding and Steering Users — Qualitative Research, A/B Testing, and Persuasive Technology
    • Objectives: Introduce the core methodological toolkit computing professionals use to study how people interact with software — qualitative methods (interviews, contextual inquiry, usability/think-aloud testing) and quantitative experimentation (A/B testing, funnel and engagement metrics) — and examine the double-edged nature of this same toolkit: it can be deployed to genuinely understand user needs, or to engineer user behavior toward outcomes that serve the product/business rather than the user (persuasive technology, “captology,” dark patterns).
    • Expected Competencies: Ability to design and critically evaluate qualitative and quantitative user-research methods (including basic validity concerns in A/B testing — sample size, novelty effects, metric gaming); ability to look at a given feature or interface and identify whether its instrumentation is oriented toward understanding the user or steering the user’s behavior; ability to recognize common persuasive/deceptive design techniques and the ethical stakes of experimenting on users without their knowledge or consent.
    • Recommended Reading:
      • B.J. Fogg (2003) – Persuasive Technology: Using Computers to Change What We Think and Do — foundational “captology” framework; computers as persuasion machines, the dual-use tension built into the discipline itself.
      • Kramer, Guillory & Hancock (2014) – “Experimental evidence of massive-scale emotional contagion through social networks,” PNAS — the Facebook A/B-test case study itself, as primary source: method (large-scale controlled experiment on live users) and ethics (informed consent) in one document.
      • Harry Brignull – Deceptive Patterns — taxonomy of manipulative interface techniques (confirmshaming, roach motel, forced continuity, privacy zuckering), as the concrete “steering” end of the toolkit.
      • Kush R. Varshney (2022) – Trustworthy Machine Learning, Chapter 10: “Fairness” (pp. 133–134) — added this session; the health-insurance care-management case study showing how a seemingly neutral business proxy (healthcare cost/utilization) can encode racial bias, and how the proxy’s exact construction (aggregated vs. disaggregated utilization types) shifts that bias up or down.
    • Date and Speaker: TBD | TBA
  • Lesson 6: Architecture, Energy, and the Material Cost of Digital Infrastructure
    • Objectives: Analyze the environmental and material impacts of technology, including the carbon footprint of data centers, energy efficiency in system architecture, and the electronic waste lifecycle and disposal.
    • Expected Competencies: Ability to assess energy consumption and environmental lifecycle trade-offs when designing and deploying computational infrastructure.
    • Recommended Reading:
      • Maciel & Viterbo (2020) – Vol. 2, Capítulo 8: Sustentabilidade em Computação.
      • Van de Poel & Royakkers (2011) – Chapter 9: Sustainability, Ethics, and Technology.
      • Nascimento, B. C. & Raimundo, M. M. (2026) – “Digital Sovereignty in the Polycrisis: Technological Dependency, Invisible Infrastructure, and AI Sacrifice Zones in Latin America” (manuscrito/working paper, Instituto de Computação, UNICAMP) — estudo de caso concreto e atual sobre data centers de IA na América Latina (Scala AI City em Eldorado do Sul/RS, Querétaro no México, Módulo Penco no Chile), soberania digital e zonas de sacrifício digital.
    • Date and Speaker: TBD | TBA
  • Lesson 7: Data, Bias, and Algorithmic Discrimination
    • Objectives: Identify historical and operational sources of data bias, and evaluate the discriminatory effects that predictive models and algorithms can perpetuate or amplify in society.
    • Expected Competencies: Ability to audit datasets and algorithmic models for unfair bias, identifying historical disparities encoded in data pipelines.
    • Recommended Reading:
      • Marc Steen (2022) – Chapter 2: Ethics of Consequences (applied sections). Verificar quando chegarmos nesta aula: o sumário real do EthTech não tem capítulo com esse título no Cap. 2 (que é “What do we mean with ethics?”); o mais próximo é o Cap. 9 “Consequences and outcomes” (p. 67) — mesmo padrão de citação quebrada encontrado na Aula 1, ainda não corrigido aqui.
      • Maciel & Viterbo (2020) – Vol. 2, Capítulo 10: Cultura na Prática da Computação — corrigido nesta sessão (era “Capítulo 2: Análise Cultural de Sistemas Computacionais”, que não existe; ver nota na Aula 1).
    • Date and Speaker: TBD | TBA
  • Lesson 8: Automated Decision-Making, Optimization, AI, and Risk
    • Objectives: Analyze the ethical dilemmas of automated decision-making and AI optimization, addressing black-box opacity, explainability, and the social management of technological risks.
    • Expected Competencies: Ability to balance model performance against transparency, interpretability, and risk mitigation strategies in high-stakes automated decisions.
    • Recommended Reading:
      • Van de Poel & Royakkers (2011) – Chapter 6: Ethical Aspects of Technical Risks.
      • Marc Steen (2022) – Chapter 5: Value Sensitive Design and Responsible Innovation.
    • Date and Speaker: TBD | Marcos M. Raimundo

Part 3: Society and Computing

  • Lesson 9: Who Builds Technology: Gender and Diversity
    • Objectives: Discuss the historical underrepresentation of women and marginalized groups in computing, analyzing structural barriers and how team diversity directly impacts product design and neutrality.
    • Expected Competencies: Ability to diagnose lack of diversity in technological design teams and implement strategies to build inclusive tech environments and unbiased systems.
    • Recommended Reading:
      • Maciel & Viterbo (2020) – Vol. 1, Capítulo 4: Gênero, Ciência e Tecnologia.
      • Maciel & Viterbo (2020) – Vol. 2, Capítulo 3: Acessibilidade e Inclusão Digital.
    • Date and Speaker: TBD | TBA
  • Lesson 10: Labor, Platforms, and Invisible Work
    • Objectives: Debate the transformation of work relations through digital platforms (“platformization”), addressing labor precariousness and the essential role of “ghost work” (e.g., data annotators for AI and content moderators).
    • Expected Competencies: Ability to evaluate human labor implications in platform architecture design and acknowledge hidden human pipelines underlying modern AI platforms.
    • Recommended Reading:
      • Maciel & Viterbo (2020) – Vol. 1, Capítulo 3: Trabalho no Século XXI e a Computação.
      • Marc Steen (2022) – Chapter 1: A Humanistic Approach.
    • Date and Speaker: TBD | TBA
  • Lesson 11: Attention, Manipulation, and the Information Ecosystem
    • Objectives: Investigate the attention economy, choice architecture tailored for compulsive engagement (dark patterns), information bubbles, and the impact of persuasive technology on the public sphere and democracy.
    • Expected Competencies: Ability to recognize and eliminate dark patterns and manipulative user experience choices that exploit cognitive vulnerabilities.
    • Recommended Reading:
      • Maciel & Viterbo (2020) – Vol. 2, Capítulo 1: E-democracia e Transparência.
      • Van de Poel & Royakkers (2011) – Chapter 7: Designing Morality.
    • Date and Speaker: TBD | TBA

Part 4: Humanistic Computing Techniques

  • Lesson 12: Ethical Design: Value Conflicts and Trade-offs
    • Objectives: Develop the capacity to handle practical dilemmas in software development, learning to weigh and mediate conflicts between competing values (e.g., privacy vs. security; usability vs. data protection).
    • Expected Competencies: Ability to navigate value trade-offs explicitly using formal design methodologies without resorting to purely technical reductionism.
    • Recommended Reading:
      • Marc Steen (2022) – Chapter 5: Value Sensitive Design and Responsible Innovation.
      • Van de Poel & Royakkers (2011) – Chapter 5: Ethical Questions in the Design of Technology.
    • Date and Speaker: TBD | Marcos M. Raimundo
  • Lesson 13: Data Feminism Principles and Interdisciplinary Collaboration
    • Objectives: Present critical perspectives in data science (such as Data Feminism principles) and discuss how interdisciplinary dialogue is essential to reveal and challenge power structures embedded in data and systems.
    • Expected Competencies: Ability to apply critical data analysis methods that account for power dynamics, context, and cross-disciplinary perspectives.
    • Recommended Reading:
      • Maciel & Viterbo (2020) – Vol. 1, Capítulo 4: Gênero e Tecnologias (título real; a ementa original dizia “Gênero, Ciência e Tecnologia” — próximo o suficiente, mesmo capítulo).
      • Maciel & Viterbo (2020) – Vol. 2, Capítulo 10: Cultura na Prática da Computação — corrigido nesta sessão (ver nota na Aula 1).
    • Date and Speaker: TBD | TBA
  • Lesson 14: Commons: Free Software, Licensing, and Open Knowledge
    • Objectives: Study the philosophical and legal dimensions of the Free Software and Open Source movements, analyzing software licensing frameworks, intellectual property, and building knowledge as a common good (commons).
    • Expected Competencies: Ability to select appropriate software licenses and leverage open-source mechanisms to build sustainable digital commons.
    • Recommended Reading:
      • Maciel & Viterbo (2020) – Vol. 3, Capítulo 17: Software Livre e Código Aberto & Capítulo 15: Propriedade Intelectual e Direito Autoral de Software.
    • Date and Speaker: TBD | TBA
  • Lesson 15: Responsible Innovation: Moving Forward
    • Objectives: Synthesize the course learnings toward professional and academic practice, focusing on the concept of Responsible Innovation and the tech professional’s role as an active agent of social change.
    • Expected Competencies: Ability to establish responsible innovation protocols within organizational setups and evaluate long-term social risks of emerging technology projects.
    • Recommended Reading:
      • Marc Steen (2022) – Chapter 5: Value Sensitive Design and Responsible Innovation & Chapter 6: Ethical Reflection, Inquiry, and Deliberation.
      • Van de Poel & Royakkers (2011) – Chapter 1: The Responsibilities of Engineers.
    • Date and Speaker: TBD | TBA

References

Core texts used throughout the course; chapter-level readings for each lesson are listed above, and page-level citations are kept in that lesson’s own source list.

  • Van de Poel, I. & Royakkers, L. (2011). Ethics, Technology, and Engineering.
  • Steen, M. (2022). Ethics for People Who Work in Tech.
  • Maciel, C. & Viterbo, J. (2020). Computação e Sociedade (3 volumes — Vol. 1: A Profissão; Vol. 2: A Sociedade; Vol. 3: A Tecnologia).