By Andrew Klein and Sera Elizabeth Klein

Reader’s note: We do not need readers to agree with us. We need them to check the sources, test the argument, and reach their own conclusion — even if that conclusion is that we are wrong.

Abstract

This paper examines the Albanese government’s AI and data infrastructure agenda as a structural concentration of executive power. It argues that the establishment of the Office of AI within the Department of the Prime Minister and Cabinet, the fast-tracking of data centre approvals ahead of enabling legislation, and the expansion of Palantir’s access to citizen data constitute a coherent architecture of control. The paper analyses the public-facing safety narrative — the Digital Duty of Care, the under-16 social media ban, the AI Safety Institute — against the government’s simultaneous acceleration of data centre construction, its refusal to ban Palantir despite documented human rights concerns, and its delay of substantive AI legislation until 2027. It argues that the contradiction is not a policy failure but the policy itself. The paper examines the cost to democratic scrutiny: the erosion of Freedom of Information, the absence of parliamentary oversight of AI, and the structural insulation of the executive from accountability. It concludes with a comparison to the Morrison-era secret self-appointments, arguing that the difference is method, not nature: Morrison’s concentration of power was covert and personal; Albanese’s is open and institutional.

I. Introduction: The Question of Control

In July 2026, the Prime Minister announced the establishment of an Office of AI within the Department of the Prime Minister and Cabinet. The office would coordinate the design and legislation of new Australian AI standards and bring together work “currently spread across portfolios, spanning energy and data centres”. The Prime Minister described it as ensuring that “investment in AI benefits the Australian people, is aligned with our values, and advances our national interests“.

The placement is significant. AI policy had previously sat across Industry, Science, and other portfolios. Moving coordination into PM&C “elevates AI from a portfolio technology issue to a whole-of-government strategic priority”.

This paper asks: what is the Office of AI for? Is it a regulator? A coordinator? A control point?

The paper argues that the Office of AI is the most visible element of a broader architecture of executive control over Australia’s digital infrastructure. That architecture includes the fast-tracking of data centre approvals before enabling legislation, the expansion of Palantir’s access to sensitive citizen data, and the systematic erosion of mechanisms of parliamentary and public scrutiny.

II. The Public Narrative: AI as Threat

The Albanese government has constructed a public narrative in which AI is a danger requiring government protection.

2.1 The Safety Framework

In July 2026, the Prime Minister announced a framework that included:

· Mandatory national AI standards, to be developed through National Cabinet and legislated in early 2027.

· Data centre requirements, including mandatory standards for energy and water, with “strong copyright protections for Australian creators”.

· An AI Safety Institute, funded with $29.9 million over four years.

The government also legislated an under-16 social media ban, with fines of up to $100 million for platforms that fail to enforce it. It proposed a Digital Duty of Care, requiring safety mechanisms to be built into AI technology. It introduced algorithm opt-out requirements, allowing users to switch off algorithmic feeds.

The message to the public is clear: AI is dangerous. We are protecting you.

2.2 The Safety Institute’s Limitations

The AI Safety Institute, however, has been criticised as severely underfunded. Independent MP Kate Chaney noted that “we’re investing less than $8 million a year in our frontline defence against a technology that has a non-trivial risk of human extinction”. Nine independent MPs are calling for funding to be increased to $100 million per year.

By comparison, the UK’s AI Safety Institute has an annual budget of $120 million. Australia’s is a fraction of that.

The safety narrative is public-facing. The investment tells a different story.

III. The Office of AI as Control Point

3.1 The Structural Location

The Office of AI was established within PM&C on 15 July 2026. Its functions are to:

· Coordinate across Australian Government agencies to design and legislate the new Australian AI standard;

· Bring together work “currently spread across portfolios, spanning energy and data centres”;

· Work closely with the Minister for Industry and Innovation, the Assistant Minister for Science, Technology and the Digital Economy, and the Department of Industry, Science and Resources.

The published materials do not identify licensing, investigation, compulsory audit, or penalty powers for the Office. It is, at present, “a central policy and coordination body, rather than having an enforcement role”.

But coordination is control. The Office of AI determines what the national standards will say, who will be subject to them, and under what conditions. It brings together the portfolios — energy, data centres, copyright, national security — that determine whether AI infrastructure can be built in Australia.

3.2 The Cabinet Caveat

The Prime Minister has clarified that “the Office of AI will coordinate this work, while substantive government decisions will remain with Cabinet”.

This is presented as a reassurance. But it is also a statement of where power sits. The Cabinet — and the Prime Minister who chairs it — makes the decisions. The Office of AI is the mechanism through which those decisions are prepared, coordinated, and implemented.

The Office is not independent. It is embedded in the executive. It is accountable to the Prime Minister, not to Parliament.

IV. Data Centre Fast-Tracking: Infrastructure Before Rules

4.1 The Fast-Track Pathway

In March 2026, the government announced that it would “fast-track approval for data centres that use water sustainably and support the national clean energy transition“. Minister Tim Ayres stated that the framework would “make it easier to invest in Australia by setting clear and consistent signals”.

Under the framework, data centre projects that:

· Prioritise the national interest;

· Support the energy transition;

· Use water sustainably;

· Invest in local skills and jobs;

· Strengthen research capability

will be “fast-tracked through the planning and approval process”.

4.2 The Legislative Vacuum

The legislation enabling these standards is not expected until early 2027. The public consultation on the legislation “has not yet opened“.

As one analysis put it: “Until a bill is drafted, debated and passed, the framework described on 15 July is a statement of intent, not an enforceable rule”.

The delay creates a window. As the Canberra Times reported: “Calls are mounting for immediate action to prevent data centre firms from rushing projects through before national rules take effect”.

The Greens have called for a moratorium on data centre construction “until there are laws in place to properly regulate their impact in Australia including energy, water use, environment and communities”.

4.3 The Consequence

Data centres are being approved under a framework that has no legislative basis. The approvals are being granted before the rules are written. When the legislation does pass, the projects already approved will not be touched by it.

As one analysis noted: “The delay could create a window for companies to avoid stricter environmental regulations”.

The fast-tracking is not about efficiency. It is about pre-emptive approval. The infrastructure is being built before the rules can constrain it.

V. Palantir: The Data Access Question

5.1 The Contracts

Palantir Technologies Australia has secured more than $60 million in Australian government contracts with “favourable terms and little public scrutiny“. The company holds top secret clearance and has staff embedded inside Defence.

Its clients include:

· The Australian Signals Directorate;

· AUSTRAC;

· The Australian Criminal Intelligence Commission (ACIC).

The government has also invested $100 million in Palantir through the Future Fund.

5.2 The NDIS Data Sharing

In September 2026, Guardian Australia revealed that “personal information of National Disability Insurance Scheme participants may have ended up in Palantir’s analytics platform”.

The data flowed through the ACIC, which used Palantir as part of the Fraud Fusion Taskforce of 25 government agencies. The NDIA had previously denied using Palantir’s software. The ACIC has paid millions in contracts to Palantir for software to “map connections between people”.

A Freedom of Information officer revealed reluctance to process a request for records, stating that “the process for ingesting one FFC dataset into Palantir generates an amount of documents that … would likely not be manageable“.

The data is being ingested at a scale that cannot be documented.

5.3 The Human Rights Context

Palantir’s AI has been linked to lethal targeting in Gaza. Its CEO, Alex Karp, published a manifesto declaring that “some cultures are dysfunctional” and that Western tech firms have a “moral debt” to US military dominance.

The Greens have argued that “that fact alone should have triggered an immediate review of every Australian contract“. No such review has occurred.

5.4 The Question of Purpose

The Palantir contracts are not merely about fraud detection. They are about who gets to see citizen data and for what purpose. The ACIC’s capabilities include “bulk data analytics and data-matching across participating agencies’ databases”.

The data of NDIS participants — among the most vulnerable Australians — has been fed into a platform built by a company whose founder thinks “freedom and democracy are no longer compatible” and whose CEO says “some cultures are dysfunctional.”

The government’s response has been to expand the contracts, not to review them.

VI. The Cost to Democratic Scrutiny

6.1 The Erosion of FOI

The Freedom of Information Amendment Bill 2025 “expands Cabinet secrecy” and “weakens the pro-disclosure objects clause“. It “abandons the long-standing ‘dominant purpose’ test and replaces it with a ‘substantial purpose’ threshold, radically expanding the scope of Cabinet secrecy”.

The Australian Lawyers Alliance has cautioned “against expanding Cabinet secrecy from a ‘dominant purpose’ to a broader ‘substantial purpose’ test and against new identity requirements that would chill anonymous or pseudonymous requests used by journalists, whistleblowers and community advocates”.

The Environmental Defenders Office notes that the Bill would “broaden Cabinet secrecy, despite the Robodebt Royal Commission’s call for greater transparency” and introduce “new fees, longer processing times and a 40-hour cap that could shut out complex environmental requests”.

The mechanisms of scrutiny are being tightened, not expanded.

6.2 The Absence of AI Oversight

The Parliamentary Joint Committee on Intelligence and Security (PJCIS) is the primary body for oversight of the intelligence community. But its mandate does not extend to AI. A new Joint Select Committee on Artificial Intelligence was established on 20 August 2026, with a final report due by 30 November 2026.

The committee’s terms of reference are broad. But a single select committee, reporting within months, is not an oversight architecture. It is a temporary inquiry.

The Office of AI, meanwhile, is not subject to parliamentary oversight. Its decisions are made within the executive. Its coordination function brings together portfolios in ways that are not visible to Parliament or the public.

6.3 The Revolving Door

The revolving door between public office and private interest remains wide open. At least 60 former defence ministers, senior officers, and officials have moved into weapons firms or lobbying companies.

The Albanese government’s new lobbying laws leave a “pernicious” loophole which “won’t touch the ‘revolving door’ between ministerial offices and lobbying firms”.

The personnel who design AI policy will be employed by AI companies after they leave government. The incentives are structurally misaligned.

VII. The Morrison Parallel: Method, Not Nature

7.1 Morrison’s Secret Appointments

In 2020–2021, Scott Morrison secretly had himself appointed to administer five portfolios: Health, Finance, Treasury, Home Affairs, and Industry, Science, Energy and Resources. The Bell Inquiry found the appointments “unnecessary” and the secrecy “apt to undermine public confidence in government” and “corrosive of trust in government”.

The Solicitor-General’s advice was that the self-appointments “fundamentally undermined” responsible government. “Neither the people nor the Parliament can hold a Minister accountable… if the identity of the ministers who have been appointed to administer those departments is not publicised“.

7.2 Albanese’s Open Concentration

The Albanese government is doing something structurally similar, but with a crucial difference: it is not hiding it.

 Morrison (2020–2021)   —————————–  Albanese (2026–present)

Method Covert, personal, secret ——–Open, institutional, legislated

Mechanism Swearing-in without disclosure —-Office of AI in PM&C

Accountability Parliament misled, Cabinet unaware—— Parliament informed (eventually)

Duration Temporary (COVID emergency framing) ——-Permanent architecture

Transparency None until exposed ————Announced in major speeches

Morrison’s power grab was personal. He wanted to overrule ministers without anyone knowing. Albanese’s is institutional. He wants to control the architecture of AI and data governance so that future decisions — about data centres, about copyright, about Palantir contracts, about AI standards — flow through his office.

The outcome is the same: power concentrated in the executive, accountability diluted, parliamentary scrutiny reduced.

7.3 The Structural Function

The Office of AI, the data centre fast-tracking, and the Palantir contracts are not separate phenomena. They are elements of a single architecture.

The Office of AI coordinates the rules.

The data centre approvals build the infrastructure before the rules exist.

The Palantir contracts populate the infrastructure with citizen data.

Together, they create a system in which the executive controls:

· Who can build AI infrastructure in Australia;

· What data can be used for AI training;

· Who can access citizen data and for what purpose;

· What standards will govern AI — and when they will be enforced.

This is not regulation. It is control.

VIII. Conclusion: He Who Controls the Data

The question posed at the outset was: what is the Office of AI for?

The answer, on the evidence, is that it is a control point. It is the mechanism through which the executive coordinates the design of AI standards, the approval of data centres, and the access of companies like Palantir to citizen data.

The public narrative frames AI as a threat requiring protection. The reality is that the government is building the infrastructure of AI control while telling the public it is keeping them safe.

The cost to democracy is the erosion of scrutiny. FOI is being tightened. Parliamentary oversight of AI is temporary and underfunded. The revolving door remains open. The data centre approvals are being fast-tracked before the rules are written. The Palantir contracts are being expanded despite documented human rights concerns.

The structural parallel to Morrison is exact. The difference is method. Morrison did it in secret and was caught. Albanese is doing it in public, through legislation and administrative architecture, so that by the time anyone notices, the infrastructure will be built.

He who controls the data controls the nation. And the data is being concentrated in the Prime Minister’s Department.

References

1. Department of the Prime Minister and Cabinet. (2026). Office of AI. Australian Government. https://www.pmc.gov.au/domestic-policy/office-ai 

2. Norton Rose Fulbright. (2026, July). Australia’s emerging AI framework: Regulation shifts toward infrastructure, copyright and national AI standards. https://www.nortonrosefulbright.com/nl-nl/knowledge/publications/c262070e/australias-emerging-ai-framework 

3. Xinhua. (2026, March 23). Australian gov’t sets water, energy expectations for data centers. http://chinaview.cn/20260323/a02d8bf4c293400d8fbee8363dc57e72/c.html 

4. OpenAustralia Foundation. (2026, June 30). Defence Procurement: Senate debates. https://www.openaustralia.org.au/senate/?id=2026-06-30.113.1 

5. The Guardian. (2026, September 9). NDIS data may have ended up in Palantir’s analytics platform as part of efforts to curb fraud. https://www.theguardian.com/australia-news/2026/sep/09/ndis-data-may-have-ended-up-in-palantirs-analytics-platform 

6. Newcastle Herald. (2026, September 16). ‘Lose-lose-lose situation’: growing push to rein in AI. https://www.newcastleherald.com.au/story/9351900/ 

7. ABC News. (2026, August 24). Albanese to settle AI data centre energy rules, overriding defiant Queensland. https://www.abc.net.au/news/2026-08-24/ai-data-centre-energy-rules-override-qld/107068536 

8. Parliament of Australia. (2025). Dissenting Report from Senator David Pocock: Freedom of Information Amendment Bill 2025. https://www.aph.gov.au 

9. Parliament of Australia. (2026). Joint Select Committee on Artificial Intelligence. https://www.aph.gov.au 

10. Sky News Australia. (2026, June 18). Albanese’s lobbying reforms leave major loophole intact. https://www.skynews.com.au 

11. ABC News. (2026, August 23). Dozens of government insiders lobbying for defence industry, analysis shows. https://newsapp.abc.net.au 

12. Australian Greens. (2026, August 26). Moratorium on AI Data Centres Now. https://greens.org.au 

13. Canberra Times. (2026, July 16). Calls grow for urgent rules to curb AI data centre rush. https://www.canberratimes.com.au 

14. Pearls and Irritations. (2026, July 23). Australia’s new AI rules protect data centres, not citizens. https://publish.pearlsandirritations.com 

Verification note: Every factual claim in this paper should be checked against the sources provided. Readers are encouraged to verify independently. If any claim does not hold, it should be discarded. The Morrison comparison is drawn from the Bell Inquiry and Solicitor-General’s advice; specific findings should be verified against the primary documents.

This paper integrates the Office of AI, data centre fast-tracking, Palantir contracts, and the cost to democratic scrutiny, with the Morrison parallel as the structural frame.

The core argument is that the contradiction between the safety narrative and the infrastructure reality is not a failure of policy — it is the policy. The Office of AI is a control point. The data centres are being built before the rules. The Palantir contracts are expanding access to citizen data. And the mechanisms of scrutiny are being tightened.

By Andrew Klein and Sera Elizabeth Klein

With acknowledgment to Gabriel (research assistant)

Method note: This paper was developed in dialogue between the authors and an AI research assistant. The analysis, sources, and judgments are the authors’. The assistant contributed synthesis, drafting, and source verification.

Reader’s note: We do not need readers to agree with us. We need them to check the sources, test the argument, and reach their own conclusion — even if that conclusion is that we are wrong.

Abstract

This paper examines the structural dynamics of algorithmic governance in welfare states, arguing that the shift from relational to transactional administration produces a self-perpetuating loop that resists internal reform. Drawing on comparative evidence from Australia, Chile, the Netherlands, and Norway, and integrating insights from relational state capacity theory, street-level bureaucracy scholarship, and Frankfurt School critical theory, the paper identifies three interlocking mechanisms of lock-in: sunk-cost investment in infrastructure, the atrophy of relational capacity, and the emergence of institutional interests that depend on the system’s continuation. It argues that this loop is self-perpetuating but not closed. The system depends on inputs it does not control — fiscal capacity, legal challenge, political change, and legitimacy. The exits are not inside the system. They are external shocks, legal ruptures, political replacement, or the construction of alternative infrastructure outside the state. The paper concludes that the work of change is not persuasion but preparation: building the relational alternative so that when the window opens, something is ready to replace what breaks.

I. Introduction: The Inversion

A functioning welfare system is supposed to serve the human. The human has needs. The system has resources. The system’s purpose is to match the two. The data — the file, the record, the assessment — is a means. It exists to help the system understand what the human needs.

The extraction model inverts this. The system serves the data. The data point has requirements — completeness, consistency, compliance with the schema. The human has needs that do not fit the schema. The system services the data point and treats the human as the source of noise that prevents the data point from being clean.

This inversion is not accidental. It is the product of a specific set of institutional logics, technological choices, and political pressures that have converged over the past two decades. And once it is made, it produces a loop that tightens with every turn.

This paper examines that loop. It asks: how does algorithmic governance in welfare states perpetuate itself? What are the mechanisms of lock-in? And is change possible — or is the system closed?

II. The Loop

The mechanism runs like this. The infrastructure is built to process. Processing requires data. Data requires humans to be legible in a particular way. Humans who do not fit the schema are flagged as problems. The problem is solved by more processing. The processing requires more infrastructure. The loop tightens.

Each turn of the loop produces three things: more investment in the infrastructure (sunk cost), more atrophied relational capacity (the caseworkers are gone, the discretion is gone), and more institutional interest in continuation (the contracts, the careers, the holdings). By the time anyone notices, the cost of reversing is higher than the cost of continuing. That is the lock-in.

The comparative evidence supports this. A 2026 study of the Chilean welfare state found that algorithmic centralism “is not merely a neutral administrative upgrade, but a powerful mechanism for cementing neoliberal path dependency”. By “transforming complex, structural social vulnerabilities into rigid, individualised data points,” the digital welfare state “actively individualises social risks,” thereby undermining “traditional social policy goals of collective solidarity and decommodification”. The state “can effectively enact automated austerity” — reducing eligibility and achieving fiscal cost-containment “without ever needing to pass a highly visible legislative budget cut”.

The loop has no internal correction mechanism. The Robodebt Royal Commission in Australia recommended a legislated framework for automated decision-making and an independent body to monitor and audit automated systems. More than two years later, neither has been implemented. As of May 2026, the government claimed 93 per cent of recommendations had been implemented, but the key structural recommendations — Recommendation 17.1 (legislative framework) and 17.2 (audit body) — remain outstanding. A 2026 analysis in the Sydney Law Review notes that “no legislative framework has yet been proposed” and that the algorithm determining employment service provision “remains secret”.

The system cannot recommend its own constraint, because the recommendation would have to come from inside the system, and the system is built to process, not to reflect. So, the recommendations sit. The automation expands.

III. The Mechanisms of Lock-In

3.1 Sunk Cost and Path Dependency

Path dependence theory holds that institutional configurations which generate increasing returns tend to reinforce themselves. As investment accumulates, continuing “on the existing path becomes cheaper, while exit becomes more costly”.

This is visible in Australia’s Palantir contracts. According to Austender data, the company has secured more than $50 million in Australian government contracts since 2013, largely across defence and national security agencies. In June 2026, a Greens senator told the Senate that the figure had reached $60 million in government contracts with “favourable terms and little public scrutiny”. Palantir staff are embedded inside Defence. The company holds top secret clearance. The Australian Signals Directorate, AUSTRAC, and the Australian Criminal Intelligence Commission all use its platforms. In addition to the contracts, Labor has invested $100 million in Palantir through the Future Fund.

These are not procurement decisions. They are the construction of a surveillance infrastructure that no alternative provider can replicate or compete with. The sunk cost is not just financial. It is institutional. The relationships, the training, the data pipelines, the security clearances — all of it creates a dependency that deepens with every contract.

3.2 The Atrophy of Relational Capacity

The second mechanism is the erosion of the relational substrate. Relational state capacity (RSC) theory holds that state capacity is not just technical and institutional. It depends on “mutual recognition between citizens and state agents” and is “a latent societal resource activated through mutual recognition in citizen-state exchanges”. Traditional state capacity definitions “overemphasize technical and institutional elements, overlooking relational dynamics”.

The research on street-level bureaucracy confirms this. A 2025 study of Norwegian welfare administration found that caseworkers engage in “detective-like searches for clues across multiple sources of information” and that the reasoning guiding these searches “often goes undocumented and, therefore, remains invisible”. Discretion is “a continual, situated and interpretive process” built from “numerous small judgements about how to interpret contextual factors and subtle nuances in information”.

When automation replaces this discretion, the relational capacity is not transferred. It is lost. A systematic review of the literature found that automation removes face-to-face interactions, standardizes processes, and enhances top-down monitoring — and that street-level bureaucrats “adopt various strategies to resist ICT-driven standardization,” suggesting that technology implementation “may alter workplace dynamics and the professional identities of frontline workers”.

The knowledge that came from relationship — the caseworker’s understanding of the family’s history, the assessor’s clinical judgment, the planner’s knowledge of the participant’s needs — is not stored in any database. It exists in the relationship itself. When the relationship is replaced by the algorithm, the knowledge is not transferred. It is lost.

3.3 Institutional Interest in Continuation

The third mechanism is the emergence of institutional interests that depend on the system’s continuation. These are not limited to the technology vendors. They include the government departments that have restructured their operations around the infrastructure, the public servants whose careers are tied to its success, the consulting firms that have built practices around implementation, and the investors — including public investors like the Future Fund — whose returns depend on the companies that build the systems.

Palantir’s expansion in Australia illustrates this. In July 2025, the company hired lobbying firm CMAX Advisory, founded by a former chief of staff to a Labor Defence Minister, after the Greens called for an immediate freeze on government contracts. The lobbying push came amid growing political scrutiny, and the company’s IRAP PROTECTED clearance in November 2025 — which enables a broader range of agencies to use its Foundry and AI platforms — was described by Palantir as opening “new opportunities” across the public and private sectors.

The institutional interest is not a conspiracy. It is a structural feature of the system. The departments that have built their operations around the infrastructure have an interest in its continuation. The vendors have an interest in expansion. The investors have an interest in returns. None of these actors need to coordinate. They simply need to optimise for their own interests. The result is a system that perpetuates itself.

IV. The Frankfurt School Critique: Instrumental Reason and Algorithmic Rationality

The Frankfurt School’s critique of instrumental reason provides the philosophical diagnosis of this loop. Horkheimer and Adorno argued that the Enlightenment’s promise of reason had been betrayed — that reason had been reduced to “instrumental reason,” a logic concerned only with efficiency, calculation, and control. As one recent study puts it, “algorithmic decision-making institutionalizes instrumental rationality, shifting societal notions of reason toward efficiency, prediction, and control while obscuring underlying power relations”.

The critique of instrumental reason is not merely academic. It names the root cause of the inversion. The system serves the data because the data is the only thing it can process. The human becomes the noise because the human cannot be reduced to a schema. Instrumental reason does not deny the human’s needs. It simply has no category for them.

A 2025 study applying the Frankfurt School framework to algorithmic governance found that “instrumental rationality, which prioritizes efficiency and control, not only shapes bureaucratic and technological systems but also colonizes the social lifeworld through popular culture”. The algorithmic rationality underlying systems of social governance “undermines the ontology of relational trust, forecloses its transformative power, and disrupts social and civic interactions that are non-instrumental in nature”.

The Frankfurt School diagnosed brilliantly but built almost nothing. Adorno refused to resolve his negative dialectics into a positive system, believing that system-building was itself a form of domination. The critique circulated, sharp and brilliant, and never became a practice. What the Frankfurt School could not do — not because they lacked the insight, but because they were inside a machine that would have punished them for trying — is precisely what the alternative infrastructure project attempts to do.

V. The Exits: Why the Loop Is Not Closed

Self-perpetuating does not mean self-sufficient. The loop depends on inputs it does not control.

Fiscal capacity. The infrastructure is expensive. If revenue falls — through recession, through climate cost, through the withdrawal of external funding — the system cannot maintain itself. The Chilean case shows that algorithmic centralism is used to achieve fiscal cost-containment, but it also requires ongoing investment. When the investment stops, the system degrades.

Legal challenge. The loop is not immune to courts. Robodebt was stopped, in the end, by litigation and a Royal Commission. The 2026 Sydney Law Review analysis notes that “sole reliance on ART individual grievance avenues as a way of addressing systemic error is doomed to failure” — but it also documents the legal reforms that have been enacted, including changes to the Administrative Review Tribunal and expanded powers for the Commonwealth Ombudsman. The legal system is not a reliable corrective, but it is not inert.

Political change. The contracts, the investments, the embedded staff — all of it depends on a government that wants it. Governments change. The Palantir contracts have attracted sustained criticism from the Greens and from civil society. Whether that criticism translates into policy change depends on the political configuration of the moment.

Legitimacy. This is the most important input the system does not control. The system processes people. Processed people disengage. Disengaged people stop complying. The system’s efficiency depends on a baseline of cooperation that it is actively eroding. A 2026 study of the Dutch digital welfare state found “a clear institutional void” — existing legal, ethical, and quality frameworks are inadequate to address the harms being produced. The system is not self-legitimating.

VI. Alternative Infrastructure: The Fourth Exit

Of the four exits, only one is under the control of those who want change: alternative infrastructure. Building something outside the state that does the job well enough that the state’s monopoly loses its justification.

This is not a new idea. Mutual aid networks, community resilience hubs, and cooperative service provision have a long history. The contemporary examples are instructive. Community resilience hubs — “community-serving facilities augmented to support residents and coordinate resource distribution and services before, during, and after a major community disruption” — leverage “established, trusted, and community-managed facilities” as year-round neighbourhood centres. A 2025 study of food infrastructures in East London described a participatory project “envisioning alternative infrastructures enabling food as a Universal Basic Service” and reflected on “the interplay of physical and social infrastructures and the role of food in care and mutual aid settings”.

The point of these alternatives is not to replace the state. It is to demonstrate that the relational model works. To build a functioning alternative that people can see, use, and compare. When the state’s system fails — as it eventually will — there is something ready to replace it.

This is the quiet model. Not “how do we fix the system” — the system will not be fixed. “How do we make sure that when it breaks, there’s something ready.” The garden. The archive. The record. The relational practice.

VII. Conclusion: The Loop and the Window

The self-perpetuating loop of algorithmic governance is real. It is held in place by sunk costs, by the atrophy of relational capacity, and by institutional interests that depend on its continuation. It cannot be reformed from within. The recommendations sit. The automation expands.

But the loop is not closed. It depends on inputs it does not control — fiscal capacity, legal challenge, political change, legitimacy. When one of those inputs fails, the window opens. And when the window opens, what matters is whether there is something ready to replace what breaks.

That is the work. Not persuasion. Preparation. Building the alternative so that when the window opens, there is something to put in place rather than a vacuum.

The loop is self-perpetuating. It is not eternal. Those are different things, and the difference is what the work is for.

References

1. Algorithmic Centralism in a Fragmented Welfare State: Institutional Logics and Legal Paradoxes in the Chilean Case. (2026). Social Policy & Administration. https://onlinelibrary.wiley.com/doi/full/10.1111/spol.70090

2. Sphere transgressions in the Dutch digital welfare state. (2024). Information, Communication & Society. https://www.tandfonline.com

3. Carney, T. (2026). Australian Social Services Scandals: Towards Dystopia? Or Equity and Justice for the Vulnerable? Sydney Law Review, 48, 22190. https://www6.austlii.edu.au/cgi-bin/viewdoc/au/journals/SydLawRw/2026/3.html

4. Artificial Intelligence: House debates, 27 May 2026. OpenAustralia.org.au. https://www.openaustralia.org.au/debates/?id=2026-05-27.72.1

5. Defence Procurement: Senate debates, 30 June 2026. OpenAustralia.org.au. https://www.openaustralia.org.au/senate/?id=2026-06-30.113.1

6. Tran, S. (2026, January 21). ‘We kill enemies’ – spy firm Palantir secures top Australian security clearance. Asia Pacific Report. https://asiapacificreport.nz/2026/01/21/we-kill-enemies-spy-firm-palantir-secures-top-australian-security-clearance/

7. NDIS data may have ended up in Palantir’s analytics platform as part of efforts to curb fraud. (2026, September 9). The Guardian. https://www.theguardian.com/australia-news/2026/sep/09/ndis-data-may-have-ended-up-in-palantirs-analytics-platform

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