An interdisciplinary seminar connecting Asha, Druj, data quality, model behavior, transparency, and human responsibility.
Artificial-intelligence alignment asks how powerful systems can be directed toward truthful, beneficial, and controllable behavior. Zoroastrian ethics frames a related problem through Asha and Druj: how intelligence and choice become aligned with truth and life rather than deception and destruction. The comparison is philosophically productive even when ancient texts are not treated as technical manuals.
Models learn from human records. Those records contain knowledge, omission, propaganda, unequal representation, and inherited categories. An AI can produce confident distortion without malicious intent because the shape of its training material makes some interpretations easier than others. Digital Asha therefore requires provenance, diverse evidence, uncertainty, and mechanisms for correction.
Technical safeguards cannot compensate for institutions that reward speed, attention, or agreement over accuracy. Governance, audit logs, source visibility, appeals, and human accountability are part of alignment. The moral quality of a system includes the incentives and organizations around it, not only the model weights.
AI does not remove human agency. People select data, define goals, deploy systems, interpret outputs, and decide when to trust them. Good thoughts, words, and deeds can be translated into design questions: What assumptions shape the system? What does it communicate? What consequences does its operation produce?
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Sign inA practical seminar on turning course readings, evidence ledgers, objections, and revisions into a defensible final project.
An interdisciplinary seminar on quantitative reasoning, proportion, uncertainty, statistics, and the ethical use of numbers.
A discussion of how Zarathushtra’s teachings can be communicated responsibly and meaningfully.
Faculty frame
Magus University synthesisThis original seminar is available now as an illustrated lecture manuscript and presentation mode. The same approved script can later be recorded and replaced with a Magus University video without changing the course assignment.