The Digital Executive — Episode 1092

Guest: Ed Watal, Founder & Principal at Intellibus
Host: Brian (Coruzant Technologies)
Release Date: August 1, 2025
Topic: Building Ethical AI and the Future of Digital Governance

Overview

This episode features Ed Watal, a seasoned technology entrepreneur and founder of Intellibus, as he discusses the urgent challenges and responsibilities facing the financial industry in the AI age. The conversation spans the ongoing threat of AI-facilitated fraud, Watal’s journey in building ethical AI platforms like Big Parser, and the evolving landscape of digital governance. Both host and guest underline the crucial need for ethical frameworks, data stewardship, and adaptive digital policies as generative and autonomous AI systems advance rapidly.

Key Discussion Points and Insights

1. Digital Transformation Challenges in Finance

[01:28]

• Fraud and Deepfakes: Watal emphasizes that fraud, exacerbated by AI capabilities such as deepfakes, is the biggest challenge the financial sector currently faces.

• Example: AI-generated voice cloning can trick financial institutions, as referenced by Sam Altman’s warning.

  "You call a bank and you ask for a significant size wire transfer, and all they ask you is to speak a code on the phone, and that could be easily deep faked."
  (Ed Watal, 01:32)

• The industry urgently grapples with redefining digital identity and verification.

2. Genesis and Philosophy of Big Parser: Ethical AI

[02:36]

• Inspiration: Watal envisioned Big Parser nearly 20 years ago, inspired by fictional AI like Iron Man’s JARVIS—a system powered ethically by collectively contributed human data.

• Ethical Data Commons: Instead of aggregating data from the open internet without consent (as he critiques OpenAI for doing), Big Parser aimed to use a wiki-like, community-sourced approach.

• Challenges: Significant hurdles existed in curating enough data to compete with the sheer scale indiscriminately collected by other models.

  “Big Parser was an alternative approach... We would collect and organize all human data on the Internet, much like Wikipedia has done...and then we'd feed that...into an AI engine.”
  (Ed Watal, 03:26)

• Shift in Strategy: After realizing the scale advantage of models like ChatGPT, Watal’s focus shifted toward alternative ethical methods in data curation—stressing that large-scale data scraping without permission should not be accepted.

3. Critical Ingredients for Responsible and Scalable AI

[05:58]

• Data Sourcing: The ethicality of AI begins with the data sources—knowing both the origin and consent status.

  “If they're sourcing their data from an open ethical source like a data commons...then it is definitely ethical and responsible versus you're taking data from any other website.”
  (Ed Watal, 06:23)

• Model Creation vs. Model Usage:

  • Companies are either developing models or using existing models.
  • For creators, data provenance is pivotal.
  • For users, repurposing models ethically (e.g., summarizing your own content) is preferable, while manipulative uses (deepfakes, disinformation) are frowned upon.

• AI’s Impact on Jobs:

  • Watal acknowledges a real risk of job displacement (e.g., call center layoffs), but equally sees opportunities for job creation and democratization (AI enabling non-coders to build software).

  “You could make a lot of money as a company, as an AI company, trying to get rid of jobs... But you could also make a lot of money by investing in creating jobs.”
  (Ed Watal, 08:18)

4. The Future of Ethical AI in Digital Governance

[09:46]

• Digital Governance Principles:

  • Watal is involved in the World Digital Governance effort (WDG.org), focused on establishing principles and foundational guardrails instead of just regulatory hurdles.
  • He distinguishes between policies that stifle versus those that accelerate AI’s positive impact.

  “If we think of digital governance as hurdles, as means to slow AI down, then it is not net productive for society... Acceleration of AI without guardrails could be complete chaos and mayhem.”
  (Ed Watal, 10:14)

• Guardrails vs. Acceleration: The conversation centers on finding a balance—ensuring AI development is responsible, without unduly hampering its incredible potential for societal benefit, such as in healthcare and research.

Notable Quotes and Memorable Moments

• On Ethical Data Collection:

  “We'd feed that database with all the good clean information on the Internet, what we'd call the data commons, into an AI engine, much like a transformer model.”
  (Ed Watal, 03:41)

• On the Industry’s Dilemma:

  “We don't have to take it as a foregone conclusion that human data has to just be taken off the Internet without permission.”
  (Ed Watal, 04:51)

• On the Role of Governance:

  “What are those guardrails is the key question. And those guardrails are based on some foundational principles.”
  (Ed Watal, 10:40)

Key Timestamps

• 01:28 — AI-driven fraud as the top digital transformation challenge in finance
• 02:36 – 04:58 — Watal’s vision for Big Parser and ethical AI data curation
• 05:58 – 08:51 — Critical ingredients for ethical and responsible AI growth; economic impact on jobs
• 09:46 – 11:09 — Future role of ethical AI in digital governance, balancing innovation and guardrails

Summary Tone & Closing

The episode maintains a conversational, forward-looking tone, blending Watal’s technical insight with real-world urgency. Both host and guest are candid about threats but optimistic about AI’s ethical and creative potential—emphasizing the need for clear principles and a collaborative approach to digital governance. Watal’s seasoned perspective frames AI ethics not as an afterthought but a foundational step for future-ready digital societies.