Case 3: The Ethics Template — Innovare AI Analysis

As you read — hold this question

What happens to an ethical framework when the organisation using it is not acting in good faith?

8M+

active Flybuys members — the data source behind the Palantir deployment

$15.7M

ACCC settlement, Jan 2025 — Coles misled consumers on "Down Down" prices

Is this workforce efficiency — or the infrastructure for retail surveillance capitalism?

The framework — Module 1

Quiz: Ethics

The Netflix ethical template

A three-step lens for evaluating AI deployments. Walk through benefits, surface the challenges, then assign accountability. Clean, teachable — and widely used.

✦

Step 1 — Benefits

What does the AI system enable? Who gains, and how? Map the upside before mapping the risk.

⚡

Step 2 — Challenges

What harms does the system create or enable? Who bears the cost — and are they the same people who get the benefit?

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Step 3 — Ethics & Accountability

Who is responsible for the outcomes? What governance, redress, and transparency exists? This step assumes the deploying organisation is trying to answer honestly.

But — a note on the template's own author

Netflix is not a neutral framing device. The template is useful — but it comes from a company that is itself on a slope it hasn't resolved. The difference between Netflix and TikTok today is degree, not direction. The underlying architecture is identical. What changed is the economic incentive — and for Netflix, that changed in 2022.

2016

Netflix (subscription)

Objective: retain subscribers

"Our biggest competitor is sleep" — Reed Hastings, 2019

2022 →

Netflix + ads tier

Objective: maximise watch time for impression revenue

Same algorithm. New economic incentive.

Precedent

YouTube

Objective: maximise session length — radicalisation a documented side effect

Watch-time algorithm + ads = same path.

Destination?

TikTok / Instagram

Objective: maximise emotional arousal — 41 state AGs, case law, Australia's under-16 ban

Degree differs. Direction does not.

Applied — Coles Supermarkets + Palantir Foundry (Australia, 2023–)

Run the template. Watch step three break.

Coles deployed Palantir's Foundry + AIP platform to process operational data at scale — workforce scheduling, inventory, shrink reduction. Running the Netflix template looks fine for the first two steps.

Benefits

✓Workforce scheduling optimised across 800+ stores — right people, right shifts, lower overtime cost

✓Inventory managed in real time — reduced waste, better shelf fill rates, lower shrink from theft

✓Price and promotion decisions informed by granular demand data — not gut-feel category management

✓Customers benefit from shorter queues, better stock availability, and — in theory — lower prices

Challenges

⚠Workforce surveillance — staff shift decisions, performance metrics, and store movement can be tracked at granular level

⚠Customer profiling — 8M+ Flybuys members linked to every purchase creates a complete behavioural dataset

⚠Algorithmic management — workers may have no recourse when a system, not a manager, denies their preferred shift

⚠Retail media monetisation — Coles 360 sells targeted ad placement to brands using the same purchase data

Ethics & Accountability

·Coles states the system is for operational efficiency and loss prevention

·No public disclosure on which data feeds Coles 360 retail media targeting vs operational use

·Workers have no disclosed mechanism to query or appeal system-generated scheduling decisions

⚠ Template assumption failure

This step asks: who is accountable and are they trying to get it right? The template cannot answer that question for Coles. In January 2025, a Federal Court accepted Coles' $15.7M settlement for systematically misleading consumers on pricing — while their "Down Down" campaign was active. The ethics step requires a good-faith actor. The ACCC found one who wasn't.

The conundrum

Stated purpose vs what the system enables

The Netflix template takes the deploying organisation's stated purpose as its starting point. Toggle between what Coles says — and what Palantir Foundry actually makes possible.

Workforce

Optimise staff scheduling across the store network

Reduce overtime and agency labour costs

Match labour to demand patterns

Operations

Reduce shrink — theft, waste, and spoilage

Improve inventory accuracy and shelf fill

Better customer experience through operational efficiency

Source: Coles Group 2023 technology partnership announcement; Palantir AIP case study materials.

Customer intelligence

Complete purchase history for 8M+ Flybuys members — every SKU, every visit, basket size over time

Behavioural segmentation — who buys on promotion vs full price, brand vs private label, frequency patterns

Predictive demand sensing — know what customers will buy before they know they want it

Monetisation capability

Coles 360 retail media network — brands pay to reach Coles shoppers using purchase-based targeting

Dynamic pricing enablement — demand data enables precision pricing that customers cannot easily verify

Worker performance profiling — granular productivity data across 120,000+ employees

These capabilities are not confirmed as active deployments. They represent what Palantir Foundry + Flybuys data technically enables. This is precisely what the ethics template cannot evaluate when the deploying organisation controls the disclosure.

The gap the template can't close: Coles controls what it discloses about how this data is used. The Netflix ethical template relies on that disclosure being accurate and complete. After a $15.7M finding of systematic consumer deception, "trust what the company says" is not an analytical position — it's a policy choice.

Before running the template — the hidden prerequisite

The check the framework doesn't ask you to make

✓

AI system is operating at material scale

Palantir Foundry processes 10B+ rows of operational and customer data across Coles' store network. Scale confirmed.

✓

Stated purpose is socially useful

Workforce efficiency, inventory accuracy, shrink reduction — all legitimate operational goals with genuine consumer benefit if delivered.

✓

Technology is fit for the stated purpose

Palantir Foundry is one of the most capable enterprise analytics platforms available. Technically well-matched to the use case.

✗

Deploying organisation has demonstrated good faith in consumer dealings

Federal Court, January 2025: Coles accepted a $15.7M settlement for misleading consumers on "Down Down" pricing over an extended period — raising prices, then reducing them to prior levels while marketing this as savings. The misconduct was systematic, not incidental.

Template prerequisite fails at step 4

The Netflix ethical template's accountability step cannot function when the actor's good faith is in question. The template produces analysis — not assurance.

Where the framework breaks

The Netflix template's unspoken assumption

Framework hole — good faith is assumed, not verified

The Netflix ethical template maps benefits, challenges, and accountability in sequence. What it doesn't do is ask you to verify whether the company running the analysis is a reliable narrator of its own intentions. The template was designed for good-faith organisations that want to identify and address the ethical dimensions of AI. Applied to an organisation with a documented history of consumer deception, the ethics step becomes an exercise in PR review — not ethical analysis.

There is a second hole the Coles case doesn't surface but the Netflix slope does: the template also has no mechanism for ethical drift over time. An organisation can be a genuinely good-faith actor in year one and structurally compromised in year five — not through malice but through incentive change. Netflix in 2016 (subscription only, aligned with viewer satisfaction) and Netflix in 2026 (ad-supported tier, aligned with engagement time) are different ethical entities operating the same algorithm. The template, run once at deployment, cannot track that. TikTok's For You Page was almost certainly not designed to push self-harm content to teenagers — it was designed to maximise engagement, and that objective produced the outcome. By 2024, 41 US state attorneys general were suing Meta for it, and Australia had passed world-first legislation banning under-16s from social media entirely. The trajectory from recommendation algorithm to legal action is not exceptional. It is what happens when engagement maximisation meets vulnerable users at scale.

The fix the template needs is two things: a prerequisite check on actor good faith — and a periodic re-run as incentive structures change. A one-time ethical analysis at deployment is not ethics governance. It is a press release.

Take this away

The Netflix ethics template assumes the organisation running it wants good outcomes—Coles and Palantir show that when that assumption fails, the template becomes a due-diligence cover story rather than an ethical safeguard.

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Case 4: Human-AI Collaboration →

Quick recall — without looking back

Test yourself on this case

Question 1 of 3

What are the three steps of the Netflix ethical template, and what does each require?

Step 1—Benefits: identify who benefits from the AI deployment and how (users, business, society). Step 2—Challenges: identify the harms, risks, and failure modes. Step 3—Accountability: identify who is responsible when something goes wrong and whether they have the authority and information to act on that responsibility. The template is designed to be run before deployment.

Question 2 of 3

Which step breaks when you apply the template to the Coles/Palantir deployment, and why?

Step 3—Accountability—breaks first. Palantir’s system connects Coles’ loyalty data to operational decisions in ways that distribute accountability across three parties: the algorithm makes recommendations, Palantir designed it, Coles deployed it—but no single party is clearly accountable for a discriminatory outcome. Step 1 also shows tension: the stated benefit is operational efficiency, but the capability enabled is granular behavioural profiling of 8.5 million Flybuys members.

Question 3 of 3

What two things does the Netflix template assume but not verify?

First, good faith—the template has no mechanism to distinguish a genuine ethical review from due-diligence cover. An organisation can run all three steps and still deploy a system designed to cause the harm the template is supposed to prevent. Second, the template has no mechanism for ethical drift over time. An organisation can be a genuinely good-faith actor at deployment and structurally compromised five years later through incentive change—Netflix itself demonstrates this across its subscription and ad-supported eras.

Sources

Netflix template: Module 1 course materials, BUSN9049. Benefits / Challenges / Ethics framework for evaluating AI deployments.
Coles + Palantir: Coles Group (2023). Technology partnership announcement. Palantir AIP deployment for operational efficiency. Coles Group Investor Relations.
ACCC settlement: Australian Competition and Consumer Commission (2025, January). Coles to pay $15.7 million for misleading "Down Down" pricing claims. accc.gov.au
Coles 360: Coles Group (2021–). Coles 360 retail media network. Purchase-data-driven advertising platform for brand partners.
Flybuys: Flybuys loyalty program (2024). 8M+ active member figure from Coles Group Annual Report 2024.
Palantir Foundry: Palantir Technologies (2023). Foundry for enterprise analytics. palantir.com