What happens when 15,000 researchers using Jupyter Notebooks for genomic research hit a wall between open science principles and federal privacy policies?
For Meag Doherty, software designer and...
What happens when 15,000 researchers using Jupyter Notebooks for genomic research hit a wall between open science principles and federal privacy policies?
For Meag Doherty, software designer and bioethics fellow, this wasn’t just a technical problem — it was an ethics problem disguised as a policy challenge.
In this On the Road episode of The New Stack Makers, Doherty sat down with TNS Editor in Chief Heather Joslyn at JupyterCon in San Diego to discuss her work launching the National Institutes of Health’s All of Us Researcher Workbench and why making ethical decisions in technology shouldn’t feel like navigating a minefield.
When Organizational Values Are Just Hallway Posters
“When things start to fall apart or decisions get made and teams are confused, it’s often because there could be a definition problem,” Doherty said. This happens, she continued, because many organizations have mission statements that exist only as hallway posters: aspirational, but disconnected from actual decision-making.
At NIH, Doherty and her team faced a concrete example: Jupyter was built to be shareable and embrace open science, but they’d configured it inside a secure environment constrained by federal policies. Sharing was technically possible, but policy compliance meant they couldn’t share publicly, primarily for patient privacy reasons.
“We want to share ‘widely and wisely,’” Doherty said, quoting her former boss. Getting there meant bringing policy stakeholders and technologists together to explore what needed to be true for sharing to happen — building internal momentum for an idea that served both open science values and patient protection.
3 Questions to Simplify Ethical Decisions
Drawing on her fellowship in bioethics at Harvard Medical School, Doherty introduced a deceptively simple three-question framework for ethical decision-making:
Who is it good for?
Why is it good?
And, most crucially, why is it bad?
That third question matters most. “Working in these new, emerging fields, it’s equally important to pause and say, where could this go wrong?” she said. “That doesn’t mean you have to stop, but I want to encourage people to do that with open eyes and open understanding of what could go wrong, and then manage against it.”
It’s the ethical equivalent of an Agile pre-mortem, and it works because it lowers the temperature around conversations that can feel overwhelming. “Talking about ethics and values can feel messy,” Doherty noted. “People hear ethics, and they think, ‘OK, she sounds like [the] legal [department], I’m not talking to her.'”
Why ‘Open’ Isn’t Always a Good Thing
Perhaps most provocative for a keynote speaker at a conference about open source technology, Doherty challenged the assumption that openness is inherently good. “Open data can mean extracted data,” she said. “Open science can feel extractive.”
When data gets into the wrong hands or is overexposed, data donors — who are often from marginalized communities — can be the ones to bear the brunt of harm. To counter this, she suggests closed feedback loops where data donors see tangible benefits, like clinical trial participants receiving free access to drugs developed from their contributions.
In the aftermath of her time at NIH, Doherty is launching a new creative studio called Both and Neither, to bring these frameworks to research software engineers and beyond to demonstrate that ethics doesn’t have to be one of the hard parts in building technology.
Check out the full episode to hear more about designing systems that are inclusive for people who aren’t in the room and why technologists already have ethics (even if they don’t realize it).
The post A 3-Question Framework for Making Ethical Tech Decisions appeared first on The New Stack.
