Use this scene from The Orbis Trilogy as a ready-to-go classroom case on algorithmic governance, responsibility, and institutional legitimacy in ethics, political science, law, or criminal justice courses. This excerpt and discussion guide may be used and shared for classroom purposes.
The excerpt below is drawn from a public testimony scene in The Final Vote, the first book in The Orbis Trilogy. It works well as a stand-alone case for 1-2 class meetings, prompting students to debate whether systems like Orbis clarify decision-making or quietly shift responsibility. It is often where readers begin actively debating the ethics of algorithmic governance and institutional legitimacy.
The chamber had never been designed for silence.
It had been built for spectacle - for voices raised and recorded, for gestures meant to be seen and archived. But now, as Mara Voss stood at the center podium, the room held something else entirely.
Expectation. Or perhaps something closer to unease.
She didn't open with a defense.
"That's the first misunderstanding," she said, her voice carrying without strain. "Orbis does not decide."
A shift in the room-subtle, but immediate.
"It reflects. It models. It reveals the consequences of choices we already have the authority to make."
A council member leaned forward. "And yet its recommendations are followed."
"They are considered," Mara corrected. "Sometimes adopted. Sometimes rejected."
"But increasingly aligned with."
Mara allowed a small pause.
"Yes," she said. "Because it is difficult to argue with outcomes when they are made visible."
Another voice, sharper this time: "Or when dissent becomes inconvenient."
There it was.
Mara didn't move away from it.
"Dissent doesn't disappear under Orbis," she said. "It becomes explicit. Quantified. Its cost is no longer abstract."
"And who decides what that cost is?"
"You do," Mara said. "All of you. All of us. Orbis doesn't create values - it processes them."
A ripple moved through the chamber. Not agreement. Not rejection. Something less comfortable.
Recognition.
She continued.
"If a policy benefits seventy percent of the population while placing strain on thirty, that tradeoff exists whether we acknowledge it or not."
"And Orbis tells us to accept that?"
"No," Mara said evenly. "It tells you that it exists."
Silence again-but this time it held.
"For most of our history, we've made decisions without fully seeing who pays for them. Orbis removes that distance."
"And replaces it with what?" someone asked. "Moral arithmetic?"
Mara met the question directly.
"With clarity."
The word landed harder than she expected.
"Clarity," the council member repeated. "Or coercion?"
"Only if truth is coercive," Mara said.
A low murmur spread across the chamber-not outrage, not approval. Something unsettled. Something thinking.
Mara didn't press forward immediately. She let it sit.
Because this was the moment that mattered.
Not whether they agreed.
But whether they understood what they were being asked to confront.
If a system reflects collective values but produces harm, where does responsibility lie?
Does making tradeoffs visible improve ethical decision-making, or complicate it?
Can a system be neutral if it shapes the conditions people live within?
Use these to open or close class discussion, or as prompts for short reflection papers.
Is Orbis simply revealing facts about our values, or does relying on it change what we value?
Can ethical decisions be meaningfully quantified, or does quantification distort moral reasoning?
Is procedural fairness sufficient for moral legitimacy?
Under what conditions, if any, can truth-telling become ethically problematic?
How would a utilitarian, a deontologist, and a virture ethicist evaluate the "70% benefit/ / 30% strain" tradeoff Mara describes?
Does using Orbis strengthen democratic accountability by making tradeoffs transparent, or weaken it by hiding decisions behind a "neutral" system?
In what ways does the council's reliance on Orbis resemble real-world uses of polls, models, or algorithms in policy-making?
Should policy prioritize optimal outcomes or perceived fairness?
How does public trust interact with technically "correct" decisions?
What happens when citizens reject systems built from their own expressed values?
When does rule-following cease to justify institutional outcomes?
How does the visibility of harm ("removing distance") affect ideas like due process, informed consent, or liability?
Can a system itself be morally accountable? If a policy recommended with Orbis's hel leads to serious harm for the 30%, who should bear legal responsibility: designers, lawmakers, administrators, or someone else?
What do institutions owe individuals harmed by lawful but damaging processes?
When does an information system become a form of coercion?
How might a system like Orbis be used in criminal justice (sentencing, resource allocation, predictive policing), and what new forms of harm might that create?
Does quantifying dissent and "costs" risk legitimizing practices that disproportionately affect certain groups?
Can a process be lawful yet epistemically dishonest?
How do "fradulent epistemic environments" persist within rule-bound institutions?
If you use this excerpt in your course, I'd love to hear how it goes and which questions resonated most with your students. You can reach me at educators@wnfort.com or through the link below.