Apr 9, 2018 · 23m · mad
The Conscience of AI // Harry Glaser, Periscope Data (FirstMark's Data Driven)
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gold bands on the timeline = statements, start to end. Hover to read, click to jump. CC turns on captions
At a DataDrivenNYC event, Periscope Data CEO Harry Glaser outlines why data professionals must act as the moral compass for AI, using case studies and governance strategies to emphasize ethical responsibility over pure profit metrics.
How this conversation actually went
Every chapter scored 0–10 on four independent dynamics. Hover any point for the reasoning behind the score. Matt holds 6.1% of the talking time here. How this is scored →
Matt as informed peer 1.7 Guest teaching 2.0 Guest disagreement 1.7 Matt pushing back 1.5
speaking balance: gold is Matt, purple is the guest (3 minute bins)
Sharpest disagreement ▶ 22:05 Rejecting tool-provider immunity
Glaser forcefully rejects the common tech defense that software vendors carry no ethical responsibility for how clients utilize their products.
Hardest push from Matt ▶ 20:37 Geopolitical advantage pushbackTurck challenges Glaser's idealistic view on corporate openness by raising the threat of global actors who ignore ethics for competitive edge.
Biggest teaching moment ▶ 14:46 Data pipeline complexity breakdownGlaser educates the room on the intricate technical realities of unifying data analysts and engineers on a single platform.
Matt holds his own ▶ 12:23 Commercial pressure on Chief Conscience OfficersTurck demonstrates domain expertise by citing the economic realities software developers face when trying to resist business incentives.
the scores for every segment, with the reasoning behind each
| Chapter | Topic | Matt as informed peer | Guest teaching | Guest disagreement | Matt pushing back | Why |
|---|---|---|---|---|---|---|
| Opening Remarks: Acceleration of AI and Machine Learning | 0 | 0 | 1 | 0 | This segment is a keynote presentation monologue by guest Harry Glaser. Because the host does not participate, host expertise and pushback are scored zero. | |
| Case Study: Facebook's Ranking Algorithm and Unintended Consequences | 0 | 0 | 2 | 0 | Glaser continues his solo talk, presenting case studies on algorithm bias, Facebook's feed ranking, and criminal AI judges. As a monologue segment, host scores remain zero. | |
| AI Applications in Healthcare and Predictive Analytics | 0 | 0 | 1 | 0 | Glaser finishes his presentation monologue highlighting positive AI applications such as Crisis Text Line. Host Matt Turck has not yet spoken during this segment. | |
| Empowering CDOs as Chief Conscience Officers and Speech Conclusion | 5 | 5 | 2 | 4 | Host Matt Turck opens the discussion by challenging the realistic power of developers and Chief Data Officers against commercial pressure, suggesting open consortia like OpenAI. Glaser elaborates on the technical roadmap for Periscope Data, educating the audience on pipeline integration. | |
| Audience Q&A: Balancing Business Incentives and Societal Good | 1 | 4 | 2 | 0 | An audience member asks how to balance profit incentives against social good. Glaser uses light sarcasm and draws on his Google experience to outline internal corporate dialogue. | |
| Audience Q&A: Corporate Transparency and Secretive Cultures | 4 | 3 | 2 | 5 | Addressing secretive corporate culture, host Matt Turck pushes back with a cynical geopolitical counterpoint about global competitors doing whatever it takes to win. Glaser acknowledges the point while remaining optimistic. |
Statements from this episode (12)
Glaser: Facebook feed algorithm generated historic business value in computing
“In fact, it would be hard to name a piece of machine intelligence that has generated more business value, maybe in the history of computing, than the rancor that the Facebook team built.”
Glaser: Data professionals must specify how their AI should be restricted
“When you build something like this, when you set out to build something like this, you start to take responsibility for how is it going to be used in the world. As you frame it out, as you put it out there, as you say to the world, here is a cool thing that te…”
Glaser: European-built facial recognition performed worse on non-European faces
“One of them is a facial recognition software, a classifier, and this particular classifier, this particular facial recognition was built by a team of folks of European descent, much like myself, and it turned out to be very good at recognizing faces of Europea…”
Glaser: Executives, customers, and governments do not understand AI technology
“I'm here to tell you as a CEO, it's not going to be your CEO, and it's not going to be your users, and it's not going to be your customers, and it's not going to be your government, because they ultimately don't know how this technology works, and they ultimat…”
Periscope Data customers spend about 20 hours per week in product
“Customers spend about 20 hours per user per week in the product.”
Crisis Text Line uses machine learning to suggest real-time volunteer responses
“They have started using machine learning to suggest answers in real time to the responders of these text messages”
Glaser: Chief Data Officers must act as corporate moral authorities
“I think chief data officers can occupy the same role at these companies. If you are thinking about eventually getting to a C-level position at your company, or if you are already a chief data officer, you can be the moral authority internally and externally fo…”
Glaser: Open dialogue yields better AI outcomes than closed corporate consortiums
“If we said the CEOs of six companies are gonna get together in a consortium and figure this stuff out, I'd be quite worried, right? But if we said, we're all going to have a series of open dialogues, and we're going to have a pretty open and transparent cultur…”
Glaser: Recent public criticism of Google's internal culture is likely deserved
“The culture there that has taken some beatings recently, I think probably deservedly”
Glaser: A company that silences ethical dialogue is a bad workplace
“And if we feel like we're not having that dialogue, and we feel like we're being told to just put our head down and go back to work and not have this conversation, That, I think, would be more problematic and, ah, evidence of a place where maybe, ah, you don't…”
Periscope Data accepts ethical responsibility for how customers use its software
“We try to reject the view that we provide a tool, and therefore we have no responsibility for the tool. You know, it's yours now. Use it. And so we try to do a few things. First of all, we try to accept responsibility for how the tool is being used and act acc…”
Periscope Data intentionally rejects black-box AI in favor of human-operated tools
“We are pretty queasy about, you know, AI in a box. Press this button, AI a thing, it'll predict for you, you're going to be great. We make a tool, we frame it as a tool for data professionals on purpose. The idea is there should be a person making these, you k…”