Human judgment, accountable systems, and responsible AI in real organizations.

Boards and executives do not fail at AI because they lack tools. They fail because accountability erodes as decisions accelerate.

Artificial intelligence already shapes hiring, pricing, compliance, product decisions, and risk exposure across organizations.

The challenge for leaders, boards, and founders is not whether to adopt AI.

It is whether the systems surrounding it support accountable human judgment once decisions accelerate, scale, or become opaque.

I work with organizations to evaluate, govern, and oversee AI-enabled systems so responsibility remains visible, decisions remain defensible, and performance remains steady under pressure.

This work sits at the intersection of law, leadership behavior, and governance.

How AI risk actually shows up

Vendor contracts that obscure responsibility for outputs, bias, or downstream use
AI tools embedded into workflows without clear decision ownership
Overreliance on vendor assurances about safety, accuracy, or compliance
Governance frameworks that exist separately from procurement, legal, and operations
Leaders expected to oversee systems they were never trained to interrogate

I coined optical ethics by design™ to describe this condition. Accountability thins once AI-managed decisions move faster than human judgment. This is where most organizations believe they have oversight and discover too late that they do not.

Effective AI governance does not live in slogans, policy decks, or one-time assessments.

It lives inside contracts, workflows, escalation paths, and human override mechanisms that still function when pressure is real.

Who this work is for

This work is designed for leaders who retain responsibility for outcomes:

Board members and advisory boards
Founders and executive leadership teams
General counsel, compliance, and risk leaders
Investors, accelerators, and mission-driven organizations deploying AI
Organizations operating in regulated or high-stakes environments

If AI touches decisions that affect people, trust, safety, or reputation, governance belongs at the center.

This work assumes retained responsibility, not delegated blame.

What I help organizations do

My work focuses on making AI governance operational, durable, and credible across technology, legal exposure, and human behavior.

The goal is not compliance theater. It is preserved accountability when things go wrong.

AI readiness and risk assessment

Identify where AI is already influencing decisions, directly or indirectly
Assess legal, operational, ethical, and reputational risk by use case
Evaluate organizational readiness to oversee AI-enabled decisions
Clarify which decisions require human review, override, or escalation

AI contract and vendor review support

Review AI vendor contracts and platform terms through a governance and risk lens
Identify gaps in accountability, audit rights, data use, model updates, and liability allocation
Pressure-test vendor representations against actual workflow and risk exposure
Support internal legal and procurement teams with issue-spotting, framing, and negotiation priorities

This work strengthens internal decision-making and governance without replacing outside counsel.

Workflow and decision architecture

Map AI-enabled workflows to decision rights and responsibility
Identify where automation increases the risk of error, bias, or diffusion of accountability
Design approval cues, human-in-the-loop structures, and override points

Governance design

Board-ready AI governance structures aligned to real operations
Clear ownership for AI-related decisions and incidents

Governance is tested when something breaks, not when everything appears to work.

Executive and board AI literacy

Build the confidence to ask informed, non-technical questions
Understand where AI tools fail, drift, or mislead
Strengthen oversight without slowing execution

Ongoing advisory support

Guidance during vendor selection, rollout, scale, or regulatory scrutiny
Decision support during moments of uncertainty or incident response
Periodic reassessment as tools, vendors, and risk profiles evolve

Decisions I help leaders and boards navigate

Should this AI system be deployed, paused, or redesigned
Whether vendor assurances are sufficient or incomplete
Where human override must be preserved
How to govern AI across decentralized teams and workflows

This work is about improving judgment before mistakes harden into exposure.

For founders and early-stage teams

AI risk often enters earlier than expected.

Founders and startups face unique challenges:

Early vendor lock-in through poorly understood terms
Over-trusting demos, benchmarks, or generic compliance claims
Building speed without decision discipline
Scaling tools before accountability is defined

I help early-stage teams build lightweight governance and vendor discipline that protects momentum without importing enterprise bureaucracy.

Why my background matters here

I bring a rare combination of experience to AI governance work:

Former Deputy General Counsel, Chief Privacy Officer, Chief Compliance Officer, and HR executive for a Fortune 500 company
Decades of experience advising organizations on risk, ethics, governance, and leadership behavior
Law professor and program designer focused on decision-making under pressure
Frequent speaker and writer on responsible AI, AI regulation, and the future of work in an AI-powered world
Retained by a global technology company as a subject-matter expert to help train advanced AI models in legal reasoning and decision-making
Advisory board member for AI-based startups

This allows me to work fluently across technical teams, legal and compliance functions, executives, and boards without diluting responsibility or oversimplifying risk.

AI navigation and governance work is typically delivered through:

Advisory board roles
Retained governance and risk advisory
AI readiness and risk assessments
AI contract and vendor review support
Executive, board, and team education

Responsible AI governance is not a framework.

It is a discipline that determines whether accountability survives scale.

When judgment is designed into systems early, organizations move faster with fewer reversals.

Request an advisory conversation.

Human judgment, accountable systems, and responsible AI in real organizations.

Boards and executives do not fail at AI because they lack tools. They fail because accountability erodes as decisions accelerate.

Artificial intelligence already shapes hiring, pricing, compliance, product decisions, and risk exposure across organizations.

The challenge for leaders, boards, and founders is not whether to adopt AI.

It is whether the systems surrounding it support accountable human judgment once decisions accelerate, scale, or become opaque.

I work with organizations to evaluate, govern, and oversee AI-enabled systems so responsibility remains visible, decisions remain defensible, and performance remains steady under pressure.

This work sits at the intersection of law, leadership behavior, and governance.

How AI risk actually shows up

Vendor contracts that obscure responsibility for outputs, bias, or downstream use

AI tools embedded into workflows without clear decision ownership

Overreliance on vendor assurances about safety, accuracy, or compliance

Governance frameworks that exist separately from procurement, legal, and operations

Leaders expected to oversee systems they were never trained to interrogate

I coined optical ethics by design™ to describe this condition. Accountability thins once AI-managed decisions move faster than human judgment. This is where most organizations believe they have oversight and discover too late that they do not.

Effective AI governance does not live in slogans, policy decks, or one-time assessments.

It lives inside contracts, workflows, escalation paths, and human override mechanisms that still function when pressure is real.

Who this work is for

This work is designed for leaders who retain responsibility for outcomes:

Board members and advisory boards

Founders and executive leadership teams

General counsel, compliance, and risk leaders

Investors, accelerators, and mission-driven organizations deploying AI

Organizations operating in regulated or high-stakes environments

If AI touches decisions that affect people, trust, safety, or reputation, governance belongs at the center.

This work assumes retained responsibility, not delegated blame.

What I help organizations do

My work focuses on making AI governance operational, durable, and credible across technology, legal exposure, and human behavior.

The goal is not compliance theater. It is preserved accountability when things go wrong.

AI readiness and risk assessment

Identify where AI is already influencing decisions, directly or indirectly

Assess legal, operational, ethical, and reputational risk by use case

Evaluate organizational readiness to oversee AI-enabled decisions

Clarify which decisions require human review, override, or escalation

AI contract and vendor review support

Review AI vendor contracts and platform terms through a governance and risk lens

Identify gaps in accountability, audit rights, data use, model updates, and liability allocation

Pressure-test vendor representations against actual workflow and risk exposure

Support internal legal and procurement teams with issue-spotting, framing, and negotiation priorities

This work strengthens internal decision-making and governance without replacing outside counsel.

Workflow and decision architecture

Map AI-enabled workflows to decision rights and responsibility

Identify where automation increases the risk of error, bias, or diffusion of accountability

Design approval cues, human-in-the-loop structures, and override points

Governance design

Board-ready AI governance structures aligned to real operations

Clear ownership for AI-related decisions and incidents

Governance is tested when something breaks, not when everything appears to work.

Executive and board AI literacy

Build the confidence to ask informed, non-technical questions

Understand where AI tools fail, drift, or mislead

Strengthen oversight without slowing execution

Ongoing advisory support

Guidance during vendor selection, rollout, scale, or regulatory scrutiny

Decision support during moments of uncertainty or incident response

Periodic reassessment as tools, vendors, and risk profiles evolve

Decisions I help leaders and boards navigate

Should this AI system be deployed, paused, or redesigned

Whether vendor assurances are sufficient or incomplete

Where human override must be preserved

How to govern AI across decentralized teams and workflows

This work is about improving judgment before mistakes harden into exposure.

For founders and early-stage teams

AI risk often enters earlier than expected.

Founders and startups face unique challenges:

Early vendor lock-in through poorly understood terms

Over-trusting demos, benchmarks, or generic compliance claims

Building speed without decision discipline

Scaling tools before accountability is defined

I help early-stage teams build lightweight governance and vendor discipline that protects momentum without importing enterprise bureaucracy.

Why my background matters here

I bring a rare combination of experience to AI governance work:

Former Deputy General Counsel, Chief Privacy Officer, Chief Compliance Officer, and HR executive for a Fortune 500 company

Decades of experience advising organizations on risk, ethics, governance, and leadership behavior

Law professor and program designer focused on decision-making under pressure

Frequent speaker and writer on responsible AI, AI regulation, and the future of work in an AI-powered world

Retained by a global technology company as a subject-matter expert to help train advanced AI models in legal reasoning and decision-making

Advisory board member for AI-based startups

This allows me to work fluently across technical teams, legal and compliance functions, executives, and boards without diluting responsibility or oversimplifying risk.

AI navigation and governance work is typically delivered through:

Advisory board roles