Data Ethics Between Vision and Reflection – Why Data Scientists Must Think Critically
What happens when algorithms make invisible decisions in our everyday lives? How much responsibility do we carry in how we use data? Episode 8 of Applied Data Science Unboxed explores how data-driven systems impact fairness, privacy, and creativity – and why data ethics and critical reflection is essential in the education of future data scientists at Lucerne University of Applied Sciences and Arts.
Podcast: Applied Data Science UNBOXED
Episode 8: Between Vision and Reflection – Why Data Scientists Must Think Critically (German only)
Host: Fabio Sandmeier
Guest: Prof. Dr. Orlando Budelacci
Shortcuts:
Biases | Data Ethics | Warning Lights | Creativity | Responsibility | Reflection | Takeaway
High above the city on the rooftop of the Lucerne School of Business, host Fabio Sandmeier meets Vice Dean of the Lucerne School of Arts and Design and Chairman of the HSLU Ethics Committee Prof. Dr. Orlando Budelacci to explore a deceptively simple question: What happens when algorithms make decisions for us? Over espresso and sunshine, they discuss invisible biases, shrinking personal agency, and the urgent need for ethical reflection in data-driven systems – not as an afterthought, but as a foundation.
00:40 – Jonas’ Morning: Five Invisible Decisions – None of Them Fair
Imagine waking up to a string of small, unfair decisions – and never even noticing them.
That’s exactly what happens to Jonas, a fictional job seeker whose morning is silently shaped by five algorithmic judgments:
- No interview invites. His CV was filtered out by a recruiting algorithm because of a six-month employment gap.
- His ride to the dentist is unusually expensive. The app marks his postal code as “less reliable” – classic location bias.
- After paying at the dentist, he receives targeted ads for painkillers and implants. His supposedly anonymous health data wasn’t so anonymous.
- His music app keeps pushing only mainstream hits, ignoring his favorites. The algorithm sees him as a data outlier.
- A credit card application is denied. No explanation. The reason? A machine learning model flagged his postcode as risky.
What connects these moments? Jonas was profiled, filtered, nudged, and judged – all before lunch. And all without transparency, explanation, or recourse. This story powerfully illustrates why data ethics matters – and how it impacts real people daily.
03:30 – On the Rooftop: What Data-Based Systems Mean for Our Freedom
With view over the rooftop Fabio Sandmeier and Prof. Dr. Orlando Budelacci discuss what Jonas’ morning says about society. According to Budelacci, data-driven systems are already deeply embedded in our everyday lives. And with them come three core data ethics challenges:
- Privacy: How much of ourselves are we giving away?
- Nudging: How subtly are we being steered toward certain choices?
- Bias: How do flawed or skewed datasets reinforce unfairness?
At the heart lies a sobering principle: Garbage in, garbage out. If the data is bad, the decisions will be too.
05:30 – Privacy, Nudging, Bias: Budelacci’s Three Ethical Warning Lights
Data systems are shifting decision-making power away from individuals. “We are no longer decision-makers,” Budelacci says. “We’re decision-receivers.”
This loss of autonomy limits our options in everyday life. Even randomness – the freedom to be surprised – is being optimized out. Dating apps, hotel recommendations, route suggestions, even crime prediction – all aim to remove uncertainty, but also reduce spontaneity and personal agency.
The challenge? Balancing the societal benefits of data with respect for individual freedom – a core concern of data ethics.
10:00 – AI and Creativity: Between Meaning and Automation
What about creativity? Even in the arts, algorithms now decide what becomes visible, what is trending, what gets funded. So, is creative work still truly human? Budelacci sees both danger and potential. On one hand, automatable creative tasks are under pressure. Algorithms can now generate decent music, text, and images instantly. On the other hand, true creativity is about meaning-making – telling stories about identity, transformation, and the human condition.
That’s where humans remain essential: selecting and interpreting data to craft narratives that matter. This intersection between creativity and data ethics is increasingly relevant across industries.
12:15 – Responsibility in the Master IDS: What Data Scientists Really Need to Know
In the MSc in Applied Information and Data Science at HSLU, students are not only taught to code, but also to think. Responsibility is a core theme. What should future data professionals learn?
- Legal literacy: Understanding current laws and upcoming regulations.
- Ethical sensitivity: Recognizing the societal impact of data-driven systems.
- Critical thinking: Questioning assumptions, biases, and systemic limitations.
As Budelacci notes: “This isn’t just about tools. It’s about understanding the world we’re building with them.”
14:45 – Ethics from Day One: How Reflection Becomes Part of Every Development
Finally, what would a future with embedded ethics look like? Budelacci’s vision: Data ethics and critical reflection becomes part of every project from day one – not an afterthought or a hurdle, but a core ingredient of good design.
That includes:
- Regular ethics reviews in development processes.
- Transparent Ethics Reports as part of business practice.
- A recognition that complexity must be handled with technology, not despite it.
In short, data ethics should not limit innovation. It should shape it.
Key Takeaway: Critical Thinking Is the New Skillset
Back on the rooftop, as the espresso cups empty, one thing becomes clear: For data scientists, technical skill is no longer enough. Reflection, responsibility, and critical awareness must be part of the job.
To avoid more mornings like Jonas’, we need professionals who can not only build smart systems – but ask the right questions about them.
- Listen to the full Episode 8 Data Ethics Between Vision and Reflection – Why Data Scientists Must Think Critically (German only)
Blog to the Podcast Applied Data Science UNBOXED
If you found this blog article on Sports Data insightful, be sure to check out our previous Applied Data Science UNBOXED blog posts!
- Read Blog Article 8 Data Ethics Between Vision and Reflection – Why Data Scientists Must Think Critically (this blog)
- Read Blog Article 7 Tactics Meet AI – When Algorithms Play a Part in Sport
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