Critical Data Studies and Societal Impact of Data Training Course

Critical Data Studies and Societal Impact of Data Training Course

Introduction

In today’s increasingly datafied world, the intersection of data, society, and ethics is more critical than ever. Critical Data Studies and Societal Impact of Data Training Course provides an in-depth exploration of how data shapes social, political, cultural, and economic systems. This course empowers participants with the analytical tools to interrogate data-driven technologies, data governance frameworks, and algorithmic decision-making processes that influence everyday life. Using real-world case studies and interactive learning methods, this course offers an interdisciplinary approach to understanding the implications of big data, surveillance, predictive analytics, and AI through a critical lens.

Participants will explore pressing topics such as algorithmic bias, surveillance capitalism, data privacy, digital inequality, and the ethical use of data in public policy and business. Grounded in theory and applied practice, the course prepares learners to recognize data injustices and advocate for equitable data practices across industries. Whether you're a policymaker, researcher, developer, or activist, this training will enhance your capacity to navigate and challenge the complex societal consequences of data-centric systems.

Course Objectives

1. Define critical data studies and its role in the digital age
2. Identify the ethical and societal implications of data collection and use
3. Analyze algorithmic bias and discriminatory data practices
4. Evaluate the impact of big data and AI on marginalized communities
5. Understand data governance, open data, and digital rights
6. Assess the role of surveillance and data capitalism in modern society
7. Explore the relationship between data infrastructures and power
8. Examine case studies of real-world data misuse and public backlash
9. Apply data justice frameworks to real-world scenarios
10. Interpret policies on data privacy, consent, and ethical usage
11. Foster inclusive, equitable, and transparent data practices
12. Develop critical thinking on tech solutionism and digital ethics
13. Design actionable strategies for responsible data innovation

Target Audience

1. Data scientists and AI developers
2. Government policymakers and regulators
3. Academics and critical theorists
4. NGO and civil society leaders
5. Journalists and digital media professionals
6. Tech company executives and product managers
7. Students in data science, sociology, or law
8. Human rights and data justice advocates

Course Duration: 5 days

Course Modules

Module 1: Introduction to Critical Data Studies

• Defining data and its sociotechnical context
• History and evolution of data-driven systems
• Interdisciplinary foundations of critical data studies
• Key thinkers and concepts in data critique
• Data as power: sociopolitical lenses
• Case Study: Facebook–Cambridge Analytica scandal

Module 2: Data Ethics and Algorithmic Bias

• Definitions and types of algorithmic bias
• Ethical dilemmas in AI and machine learning
• Discriminatory datasets and outcomes
• Auditing algorithms for fairness
• AI transparency and explainability
• Case Study: Amazon’s biased recruitment algorithm

Module 3: Surveillance, Privacy & Consent

• The rise of surveillance capitalism
• The politics of data consent
• Biometrics, tracking, and behavioral data
• Legal frameworks: GDPR, CCPA
• Corporate surveillance and user exploitation
• Case Study: China’s Social Credit System

Module 4: Data and Inequality

• Digital divide and socio-economic data gaps
• Racialized and gendered data harms
• Data colonialism and exploitation in the Global South
• Representation and inclusion in datasets
• Data bias in health, housing, and education
• Case Study: Racial bias in healthcare algorithms

Module 5: Data Governance and Policy

• Principles of open data and transparency
• National and international data laws
• Public vs. private sector responsibilities
• Data ownership and intellectual property
• Citizen data rights and advocacy
• Case Study: India’s Aadhaar ID system

Module 6: AI, Automation, and Societal Disruption

• AI’s impact on labor and employment
• Automation and digital exclusion
• Ethical challenges in predictive policing
• Future of work and algorithmic control
• Debates on technological determinism
• Case Study: Predictive policing tools and community backlash

Module 7: Resistance, Activism, and Data Justice

• Data justice movements and frameworks
• Grassroots activism for data transparency
• Community-based data projects
• Data storytelling and counter-mapping
• Ethical hacking and whistleblowing
• Case Study: Black Lives Matter and police data transparency

Module 8: Designing Ethical Data Futures

• Human-centered data design principles
• Co-creating ethical tech tools
• Building inclusive digital infrastructures
• Civic tech and participatory design
• Futures thinking and scenario planning
• Case Study: Responsible AI in urban planning

Training Methodology

• Interactive lectures with expert facilitators
• Hands-on workshops on real-life ethical dilemmas
• Group discussions for knowledge exchange and peer learning
• Case study analysis for critical reflection and application
• Capstone project to design a data justice intervention
• Feedback sessions for continuous improvement and personalization

Register as a group from 3 participants for a Discount

Send us an email: info@datastatresearch.org or call +254724527104 

Certification

Upon successful completion of this training, participants will be issued with a globally- recognized certificate.

Tailor-Made Course

 We also offer tailor-made courses based on your needs.

Key Notes

a. The participant must be conversant with English.

b. Upon completion of training the participant will be issued with an Authorized Training Certificate

c. Course duration is flexible and the contents can be modified to fit any number of days.

d. The course fee includes facilitation training materials, 2 coffee breaks, buffet lunch and A Certificate upon successful completion of Training.

e. One-year post-training support Consultation and Coaching provided after the course.

f. Payment should be done at least a week before commence of the training, to DATASTAT CONSULTANCY LTD account, as indicated in the invoice so as to enable us prepare better for you.