Beyond the Lens

01Course summary

For visual journalists, generative AI video can feel like a direct threat to core tenets of journalism. Can we use technology that generates synthetic reality to ethically tell a story? This 5-week, 1-credit module serves as an experimental lab to attempt to answer that question. We will examine the current landscape of non-fiction synthetic media through a critical lens, then move into hands-on production to determine if — and how — generative AI can serve ethical, fact-based reporting.

You'll experiment with the latest tools to create your journalism, whether that is animation or documentary re-creation without the need for actors. Perhaps it will be something completely new. The tools change by the week, so part of your job is finding the right tool for the story, not just learning one.

We'll organize our thinking around a spectrum. The further a technique moves from the camera, the heavier its ethical burden:

02Outcomes

• The current landscape of synthetic visual journalism — what's been done well, what's gone wrong and why
• A production workflow in Google Gemini Veo/Omni, from reference images to storyboard to finished shots
• Disclosure, provenance and consent: how to be transparent with your audience about what's real and what's AI
• How to reach your own evidence-based answer to the course's central question

03What you need

A Google AI Pro account. U.S. college students can currently get a free year of Google AI Pro. Claim it with a personal Gmail account, not your CUNY account, and do it before our first class so we don't lose time to logins.

Your laptop and a drive. Bring both to every class. You'll finish your piece in Premiere or the editor of your choice, so bring your project files too.

A heads-up on cost. Video AI can be very expensive. We have $5,000 worth of tokens from Google to use for the class. That is what we'll primarily use. You may want to test tools beyond Google's. Additional tools are not required.

04Diversity, equity & inclusion

I've deliberately chosen topics, examples, and assignments that ask you to engage with a diversity of voices, perspectives, and lived experiences. In this space we stay open to learning and growth and commit to treating each other with courtesy and respect.

As journalists, you'll be expected to consider people and viewpoints you don't agree with. During discussions, respect each other's unique lived experiences and points of view, aim to be thoughtfully critical of the work and not the person, and always be kind.

05Accommodations

If I can help accommodate any need or challenge — physical, social, or otherwise — please let me know. Any student who needs accommodations should register with the Office of Student Affairs in room 307 as soon as possible. Accommodations are not retroactive.

06Deadlines & attendance

All work is due Wednesday at midnight unless otherwise noted, so I can review it before Friday's class.

In journalism, deadlines arrive regularly and without mercy. Plan ahead — generating and fixing shots almost always takes longer than you think. If you're stuck, contact me at least 48 hours before a deadline and we'll work out a solution together. A late assignment automatically drops your grade by a half grade (e.g., from an A to an A-).

Attendance is mandatory. We only meet five times, so a single missed class is a big share of the course. Only a personal illness or a family emergency is a valid reason to miss a class.

07Assignments & grading

This is a seminar. You'll produce one short piece of journalism, moving through pitch → rough → final, and you'll fold my feedback on the rough into the final cut. Along the way you'll keep a production log — a running record of your sources, prompts, tools, and what's generated versus captured. With your final piece, you'll turn in a methodology statement explaining what you generated and why, the sourcing behind it, and your answer to the course's central question.

Grading

A

Turns in all work on time, comes to all classes on time, participates, and incorporates feedback from the rough edit into the final.

B

Turns in more than one assignment or exercise late, misses (or is late to) class, or doesn't incorporate feedback.

C

Consistently turns in work late, or consistently misses (or is late to) class, or fails to incorporate feedback.

F

Consistently turns in work late and misses (or is late to) class and doesn't incorporate feedback.

Pluses or minuses for students between grades.

08Week by week

This syllabus may be updated. I'll let you know if anything is added or changed.

09Fabrication, disclosure & AI

This course is the exception to the rule you've heard in every other class: here, generative AI is the medium. That makes the rest of our standards matter more, not less.

• Everything must be reported. Generated imagery has to be grounded in sourcing you can show — interviews, documents, photos, data. If you can't source it, don't generate it.
• Everything must be disclosed. Your audience should never have to guess what's real, re-created or generated.
• Keep your log honest. The production log is your record of what you did. Treat it like your notes.

If you have any doubts about something you're considering, come see me first. Better to figure out an ethically sound way to do something than to risk your credibility, reputation, and career. For the full Code of Ethics, see the Code of Ethics website.