Professional Fiduciary Duty in the Age of AI
The client eyes you across the desk, not the screen. Efficiency kneels to trust; betray it, and no algorithm absolves. Guard that human bond fiercely: Our future depends on it.
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Your client, a high profile
family-owned business is on the brink of a major merger or acquisition. They
share intricate details of their subsidiary assets, family disputes, and
strategic vulnerabilities trusting you as their go to professional.
To reduce hours off the task, you
input lots of confidential details into an AI platform for a summary, or maybe
even the first draft.
In a data centre thousands of
miles away: A polished draft is generated in seconds which would have taken
hours, if not days if done manually.
But what if, unbeknownst to you,
that AI company, which is hungry for data, absorbs every word, only to leak
fragments of your client's secret data directly or indirectly, to a rival
entity querying on a similar scenario or asking for a simulation of what their
counterpart’s strategy may be?
This risk isn't hypothetical,
it's the ticking bomb in every professional's workflow as we rush to embrace AI
without questioning its risks.
At the core of this crisis lies
the principle of fiduciary duty. Across numerous professions Lawyers, doctors,
accountants, bankers, therapists, practitioners are bound by an obligation of
confidentiality.
This duty constitutes a
relationship of trust, wherein the private concerns of clients are safeguarded
with the utmost discretion, transforming personal disclosures into protected
and sacred confidences.
Clients don't just share facts;
they bare souls, from a doctor's medical diagnosis to an accountant unearthing
a potential fraud trail.
Yet generative AI models, these
cloud-based marvels operate more like sponges than safes, absorbing every
strand of data available to improve their future outputs.
When you upload a patient's chart
or a divorce settlement, the data travels to distant servers for processing,
often fueling model improvements and training unless explicitly barred.
Consumer-grade tools, free and
abundant, rarely guarantee zero retention; your client's pain morphs into data
centre algorithms.
Professionals who engage with
this are edging towards borderline malpractice, outsourcing a non-delegable
duty to a machine that neither understands ethics nor swears oaths.
The Hidden Dangers
AI's magic stems from its
learning prowess, but that's precisely its danger. Unlike a junior associate
who forgets after filing, these models analyse patterns: Syntax, numbers,
contexts into their vast neural webs. Feed in a psychiatric evaluation or tax
return, and echoes linger.
The real horror?
"Hallucinations," where AI confidently spits fabricated facts,
blending one user's input into another's output. Imagine a forensic accountant
inputting embezzlement ledger; weeks later, the same model serves up those
exact figures to opposing entity asking about "common fraud pattern
tactics by X."
Real-world precedents chill the
spine: Tech engineers once fed proprietary code into public chatbots, only to
watch it regurgitate in competitors' queries.
For fiduciaries, this isn't a
quirky bug it's a disclosure event, piercing confidentiality with surgical
precision. Professional regulating bodies, issue stark warnings: Professionals
must audit AI tools, anonymize data, and supervise outputs. Yet in the heat of
deadlines, many gloss over terms of service, mistaking "helpful
assistant" for "sworn confidant."
Layer on data protection laws,
and the noose tightens. Regimes like the EU's GDPR, UK's Data Protection Act,
or Bangladesh's evolving digital security frameworks cast professionals as
"data controllers," liable for every byte processed by "processors"
like AI vendors or cloud giants.
Principles of purpose limitation,
minimization, and accountability demand risk assessments before any input. No
pasting sensitive files into public interfaces without safeguards—cross-border
contracts with ironclad disclaimers often leave you exposed.
A hallucinated leak in a court
filing? Regulators dissect your competence: Did you foresee risks? Secure
consents? Document impact assessments? Professional indemnity insurers balk,
ethics boards sanction, and clients sue. The margin for error? Razor-thin.
Untangling the Web of
Accountability
When the vault cracks, who pays
the price? You, the professional, sit at the apex. Fiduciary duty doesn't
evaporate with "the AI did it" excuse. Just as you're liable for a
paralegal's slip, you're the gatekeeper for tools you unleash.
AI companies hide behind beta
disclaimers and "use at your own risk" & “AI can make mistakes,
please double check” clauses; cloud hosts plead infrastructure neutrality.
Shared liability glimmers misrepresented privacy could ensnare providers under
consumer laws but enforcement falters across jurisdictions.
Multinational behemoths wield
opaque terms, rendering litigation a fool's errand. Clients, the true victims,
foot the emotional bill: shattered trust in their hour of need. We've danced
this tango before with tech leaps: telephones, emails, the internet, each
birthing new ethics. AI demands we rediscover human custodianship amid the
code.
As a corporate lawyer navigating
Bangladesh's Company Act, where board governance and contract precision rule,
AI tempts with sifting case law or drafting notices. Doctors in overcrowded
clinics crave symptom triage; accountants chase audits faster. Geopolitics and
political and economic uncertainty adds urgency: leaked strategies in tense
regions invite exploitation. Efficiency seduces, but trust is eternal. One
breached resolution could torch careers, families, futures.
Safeguards for a Secure Future
The ethical line? Bifurcate
ruthlessly.
Anonymize without mercy:
Strip identifiers, generalize before input: names, dates, figures out.
Use enterprise grade AI
subscriptions: Paid enterprise grade AI tools have policies not to retain
data after a certain number of days and delete them from their servers,
minimizing the risk of information leaks via AI hallucinations.
Vet vendors, secure consents:
Demand audited privacy warranties; inform clients explicitly of AI's role.
Embed human oversight:
Triple-check outputs; no autopilot for deliverables.
Formalize assessments:
Conduct and log data-protection impact checks, per regulatory mandates.
Build firm resilience:
Train teams, craft incident plans, consult insurers early and at regular
intervals.
Push for policy: Lobby for
AI transparency: data flow disclosures, mandatory breach reports, crisp
liabilities.
Policymakers must step up,
crafting risk-based rules that foster innovation without fragility. In
Bangladesh, aligning with global standards could safeguard our growing digital
economy.
AI isn't the villain -- it's a
force multiplier, sifting volumes of case law or medical journals in blinks.
But confidentiality isn't a relic to automate away; it's the profession's soul.
The client eyes you across the
desk, not the screen. Efficiency kneels to trust; betray it, and no algorithm
absolves. Guard that human bond fiercely: Our future depends on it.
Shafqat Aziz is a barrister
(Lincoln’s Inn) and an accredited Civil-Commercial Mediator (ADR-ODR
International).
Written by:
Shafqat Aziz
Barrister (Lincoln's Inn)
LLM Corporate Law, NTU
Industry & Alumni Fellow, NTU
PGDL, UWE Bristol
LLB, BPP University
Accredited Civil-Commercial
Mediator (ADR-ODR International)
https://www.linkedin.com/in/shafqat-aziz-29a3a5171/
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