Resh(AI)ping Good Administration: Addressing the mass effects of public sector digitalisation

Happy New Year! I hope 2024 is off to a good start for you.

My last project of last year (finished on the buzzer…) was a paper expanding the ideas first floated in the DigiCon blog post ‘Resh(AI)ping good administration: beyond systemic risks vs individual rights?’, which sparked interesting discussion at the DigiCon III conference last fall.

With a slightly different (and hopefully clearer) title, the paper is now under peer-review (and so, as always, comments welcome ahead of a final revision!).

Titled ‘Resh(AI)ping Good Administration: Addressing the mass effects of public sector digitalisation’, the paper focuses on what I think is the most distinctive feature of public sector digitalisation and the prime challenge to traditional good administration guarantees: mass effects. Its abstract is as follows:

Public sector digitalisation is transforming public governance at an accelerating rate. Digitalisation is outpacing the evolution of the legal framework. Despite several strands of international efforts to adjust good administration guarantees to new modes of digital public governance, progress has so far been slow and tepid. The increasing automation of decision-making processes puts significant pressure on traditional good administration guarantees, jeopardises individual due process rights, and risks eroding public trust. Automated decision-making has so far attracted the bulk of scholarly attention, especially in the European context. However, most analyses seek to reconcile existing duties towards individuals under the right to good administration with the challenges arising from digitalisation. Taking a critical and technology-centred doctrinal approach to developments under the law of the European Union and the Council of Europe, this paper goes beyond current debates to challenge the sufficiency of existing good administration duties. By stressing the mass effects that can derive from automated decision-making by the public sector, the paper advances the need to adapt good administration guarantees to a collective dimension through an extension and a broadening of the public sector’s good administration duties: that is, through an extended ex ante control of organisational risk-taking, and a broader ex post duty of automated redress. These legal modifications should be urgently implemented.

Sanchez-Graells, Albert, ‘Resh(AI)ping Good Administration: Addressing the mass effects of public sector digitalisation’ (December 19, 2023). Available at SSRN: https://ssrn.com/abstract=4669589.

Public procurement (entry for an Encyclopaedia)

I was invited to provide an entry on ‘public procurement’ for the forthcoming Elgar Encyclopedia of European Law co-edited by Andrea Biondi and Oana Stefan. I must say I struggled to decide what to write about, as the entry was limited to 4,000 words and there are so many (!!) things going on in procurement. Below is my draft entry with perhaps an eclectic choice of content. Comments most welcome!

The draft entry is also available on SSRN if you prefer a pdf version: A Sanchez-Graells, ‘Public procurement’ in A Biondi and O Stefan, Elgar Encyclopedia of European Law (forthcoming) available at https://ssrn.com/abstract=4621399.

Public Procurement

I. Introduction

From up close, public procurement law can be seen as the set of mostly procedural rules controlling the way in which the public sector buys goods, services, and works from the market. Procurement would thus be a set of administrative law requirements concerned with the design and advertisement of tenders for public contracts, the decision-making process leading to the award of those contracts, and the advertisement and potential challenge of such decisions. To a more limited extent, some requirements would extend to the contract execution phase, and control in particular the modification and eventual termination of public contracts. From this narrow perspective, procurement would be primarily concerned with ensuring the integrity and probity of decision-making processes involving the management of public funds, as well as fostering the generation of value for money through effective reliance on competition for public contracts.

The importance and positive contribution of public procurement law to the adequate management of public funds may seem difficult to appreciate in ordinary times, and there are recurrent calls for a reduction of the administrative burden and bureaucracy related to procurement procedures, checks and balances. However, as the pervasive abuses of direct awards under the emergency conditions generated by the covid pandemic evidenced in virtually all jurisdictions, dispensing with those requirements, checks and balances comes with a very high price tag for taxpayers in terms of corruption, favouritism, and wastage of public funds.

Even from this relatively narrow perspective of procurement as a process-based mechanism of public governance, procurement attracts a significant amount of attention from EU legislators and from the EU Courts and is an area of crucial importance in the development of the European administrative space. As procurement regulation has been developed through successive generations of directives, and as many Member States had long traditions on the regulation of public procurement prior to the emergence of EU law on the topic, procurement offers a fertile ground for comparative public law scholarship. More recently, as EU procurement policy increasingly seeks to promote cross-border collaboration, procurement is also becoming a driver (or an irritant) for the transnational regulation of administrative processes and a living lab for experimentation and legal innovation.

From a slightly broader perspective, public procurement can be seen as a tool for the self-organisation of the State and as a primary conduit for the privatisation and outsourcing of State functions. A decision preceding procurement concerns the size and shape of the State, especially in relation to which functions and activities the State carries out in-house (including through public-public collaboration mechanisms), and which other are contracted out to the market (‘make or buy’ decisions). Procurement then controls the design and award of contracts involving the exercise of public powers, or the direct provision of public services to citizens where market agents are called upon to do so (including in the context of quasi-markets). Procurement thus heavily influences the interaction between the State’s contractual agents and citizens, and becomes a tool for the regulation of public service delivery. The more the State relies on markets for the provision of public services, the larger the potential influence (both positive and negative) of procurement mechanisms on citizens’ experience of their (indirect) interaction with the State. On this view, procurement is a tool of public governance and a conduit for public-private cooperation, as well as a regulatory mechanism for delegated public-public and public-private interactions. From this perspective, procurement is often seen as a neoliberal tool closely linked to new public management (NPM), although it should be stressed that procurement rules only activate once the decision to resort to contracting out or outsourcing has been made, as EU law does not mandate ‘going to market’.

From an even broader perspective, public procurement represents a more complex and multi-layered regulatory instrument. Given the enormous amounts of public funds channelled through public procurement, and the market-shaping effects that can follow from the exercise of such buying power, procurement regulation is often used as a lever for the promotion of policies and goals well beyond the narrower confines of procurement as a regulated administrative process. In the EU, procurement has always been an instrument of internal market regulation and sought to dismantle barriers to cross-border competition for the award of public contracts. More recently, and in line with developments in other jurisdictions, procurement has been increasingly singled out as a tool to promote environmental and sustainability goals, as well as social goals, or as a tool to foster innovation. Procurement is also increasingly identified as a tool to foster compliance with human rights along increasingly complex supply chains, or to address social inequality, such as through gender responsive procurement. In the face of the challenges posed by the mainstreaming of digital technologies, and artificial intelligence in particular, procurement is also increasingly identified as a tool of digital regulation. And, against the background of rule of law challenges within the EU, procurement conditionality has added to the fiscal control effect traditionally linked to the use of EU funds to subsidise procurement projects at Member State level. From this perspective, procurement is either an enforcement (or reinforcement) mechanism, or a self-standing regulatory tool for the pursuit of an increasingly diverse array of horizontal policies seeking to steer market activities.

Relatedly, given the importance of procurement as an economic activity, its regulation is of crucial importance in the context of industrial and trade policies. The interaction between procurement and industrial policy is not entirely straightforward, and neither is the position of procurement in the context of trade liberalisation. While there have been waves of policy efforts seeking to minimise the use of procurement for industrial policy purposes (ie the award of public contracts to national champions), in particular given the State aid implications of such uses of public contracts under EU law, and while there is a general push for the liberalisation of international trade through procurement—there are also periodic waves of protectionism where procurement is used as a tool of international economic regulation or, more broadly, geopolitics. Most recently, the EU has aggressively (re)regulated access to its procurement markets on grounds of such considerations.

It would be impossible to address all the issues that arise from the regulation of public procurement in all these (and other potential) dimensions within a single entry. Here, I will touch upon some the issues highlighted by recent developments in EU law and policy, and in relation to contemporary debates around the salient grand challenges encapsulated in the need for procurement to support the ‘twin transition’ to green and digital. I will not focus on the detail of procurement rules, which is better left to in-depth analysis (eg Arrowsmith [2014] and [2018], Steinicke and Vesterdorf [2018], or Caranta and Sanchez-Graells [2021]). There are a few common threats in the developments discussed below, especially in relation to the increasing complexity of procurement policymaking and administration, or the crucial role of expertise and capability, as well as some challenges in coordinating them in a way that generates meaningful outcomes. I will briefly return to these issues in the conclusion.

II. Procurement, Trade, and Geopolitics

A constant tension in the regulation of procurement concerns the openness of procurement markets. On the one hand, procurement can be a catalyst for trade liberalisation and there are many economic advantages stemming from increased (international) competition for public contracts—as evidenced in the context of the World Trade Organisation Government Procurement Agreement (WTO GPA) (Georgopoulos et al [2017]). In the narrower context of the EU’s internal market, public procurement openness is taken to its logical extremes and barriers to cross-border tendering are systematically dismantled through legislation, such as the most recent 2014 Public Procurement Package, and its interpretation by the Court of Justice. While there is disparity in national practice, the (complete) openness of procurement markets in the EU tends to not only benefit EU tenderers, but also those of third countries, who tend to be treated equally with EU ‘domestic’ tenderers.

On the other hand, the same (international) competition that can bring economic advantages can also put pressure on (less competitive) domestic industries or create risks of uneven playing field—especially where (foreign national champion) tenderers are propped up by their States. In some industries and in relation to some critical infrastructure, the award of oftentimes large and sensitive public contracts to foreign undertakings also generates concerns around safety and sovereignty.

A mechanism to mediate this tension is to make procurement-related trade liberalisation conditional on reciprocity, which in turn leverages multilateral instruments such as the WTO GPA. This is an area where EU law has recently generated significant developments. After protracted negotiations, EU procurement law now comprises a set of three instruments seeking to rebalance the (complete) openness of EU procurement markets.

As a starting point, under EU law, only foreign economic operators covered by an existing international agreement (such as the WTO GPA, or bilateral or multilateral trade agreements concluded with the EU that include commitments on access to public procurement) are entitled to equal treatment. However, differential treatment or outright exclusion of economic operators not covered by such equal treatment obligation tends (or has historically tended to) be rare. This can be seen to weaken the hand of the European Commission in international negotiations, as EU procurement markets are de facto almost entirely open, regardless of the much more limited legal openness resulting from those international agreements.

To nudge contracting authorities to enforce differential treatment, in 2020, the European Commission issued guidance on the participation of third country bidders and goods in EU procurement markets, stressing the several ways in which public buyers could address concerns regarding unfair competitive advantages of foreign tenderers. This should be seen as a first step towards ramping up the ‘rebalancing’ of access to EU procurement markets, though it is a soft (law) step and one that would still hinge on coordinated decision-making by a very large number of public buyers making tender-by-tender decisions.

A second and crucial step was taken in 2022 with the adoption of the EU’s International Procurement Instrument (IPI), which empowers the European Commission to carry out investigations where there are concerns about measures or practices negatively affecting the access of EU businesses, goods and services to non-EU procurement markets and, eventually, to impose (centralised) IPI measures to restrict access to EU public procurement procedures for businesses, goods and services from the non-EU countries concerned. The main effect of the IPI can be expected to be twofold. Outwardly, the IPI will lead to the European Commission having ‘a stick’ to push for reciprocity in procurement liberalisation as a complement to ‘the carrot’ used to persuade more and more countries to enter into bilateral trade deals, or for them to join the WTO GPA. Internally, the IPI will allow the Commission to mandate Member States to implement the relevant restrictions or exclusions from the EU procurement markets in relation to the jurisdictions concerned. This is expected to address the issue of de facto openness beyond existing (international) legal requirements, and therefore galvanise the ability of the Commission to control access to ‘the EU procurement market’ and thus bolster its ability to use procurement reciprocity as a tool for trade liberalisation more effectively.

A third and final crucial step came with the adoption in 2023 of the Regulation on foreign subsidies distorting the internal market, which creates a mechanism for the control of potential foreign subsidies in tenders for contracts with an estimated value above EUR 250 million, and can also result in the imposition of (centralised) measures curving access to the relevant contracts by the beneficiaries of those foreign subsidies. This comes to somehow create an international functional equivalent to the State aid control in place for domestic tenders, as well as a mechanism for the EU to enforce international anti-dumping standards within its own jurisdiction.

This trend of evolution in EU public procurement regulation evidences that public buyers are increasingly constrained by geopolitical and international economic considerations administered by the European Commission in a centralised manner (Andhov and Kania [2023]). Whether this will create friction between the Commission and Member States, perhaps in relation to particularly critical or sensitive procurement projects, remains to be seen. In any case, this line of policy and legal developments generates increased complexity in the administration of procurement processes on a day-to-day basis, and will require public buyers to develop expertise in the assessment of the relevant trade-related instruments and associated documentation, which will be a theme in common with other developments discussed below.

III. Procurement and Sustainability

It is relatively uncontroversial that public expenditure has a crucial role to play in supporting (or driving) the transition towards a more sustainable economy, and most jurisdictions explicitly consider how to harness public expenditure to decarbonise their economy and achieve net zero targets—sometimes in the broader context of efforts to achieve interlinked sustainable development goals. However, the details on the specific sustainability goals to be pursued through procurement (as compared to other means of public finances, such as subsidies or tax incentives), and on how to design and implement sustainable procurement are more contested.

Green procurement has been a primary focus of EU public procurement policy for a long time now, and it has received even further increased attention in recent years, culminating in the attribution of a prominent role for the implementation of the EU’s Green Deal. EU procurement law has been increasingly permissive and facilitative of the inclusion of environmental considerations in procurement decision-making and the European Commission has developed sets of guidance and technical documentation that are kept under permanent review and update. Overall, EU procurement law offers a diverse toolkit for public buyers to embed sustainability requirements.

However, the uptake of green procurement is much lower than would be desirable and progress is very uneven across jurisdictions and in different sectors of the economy. There is a growing realisation that facilitative or permissive approaches will not result in the quick generalisation of sustainability concerns across procurement practice required to contribute to mitigating the devastating effects of climate change in a timely fashion, or with sufficient scale. Informational and skills barriers, difficult economic assessments and competing (political) priorities necessarily slow down the uptake of sustainable procurement. In this context, it seems clear that technical complexity in the administration of procurement on a day-to-day basis, and limited technical skills in relation to sustainability assessments, are the primary obstacle in the road to mainstreaming sustainable public procurement. It is hard for public buyers to identify the relevant sustainability requirements and to embed them in their decision-making, especially where the inclusion of such requirements is bound to be checked against its suitability, proportionality, and its effect on potential competition for the relevant public contract.

To overcome this obstacle, it seems clear that a more proactive or prescriptive approach is required and that sustainability requirements must be embedded in legislation that binds public buyers—so that their role becomes one of (reinforced) compliance assessment or indirect enforcement. The question that arises, and which reopens age old discussions, is whether such legislation should solely target public procurement (Janssen and Caranta [2023]) or rather be of general application across the economy (Halonen [2021]).

This controversy evidences different understandings of the role of procurement-specific legislation and different levels of concern with the partitioning of markets. While the passing of procurement-specific legislation could be easier and politically more palatable—as it would be perceived to ultimately impose the relevant burden on economic operators seeking to gain public business (and so embed a certain element of opt-in or balanced regulatory burden against the prospect of accessing public funds), and the cost would ultimately fall on public buyers as ‘responsible (sustainable) buyers’—it would partition markets and eg potentially prevent the generation of economies of scale where public demand is not majoritarian. Moreover, such market partitioning would raise entry barriers for entities new to bidding for public contracts, as well as facilitate the emergence of anticompetitive and collusive practices in the more concentrated and partly isolated from potential competition ‘public markets’ (Sanchez-Graells [2015]) in ways that general legislation would not. More generally, advances in mandating sustainable procurement could deactivate the pressure for developments in more general sustainability mandates, as policymakers could claim to already be doing significant efforts (in the narrow setting of procurement).

A narrow sectoral approach to legislating for public procurement only would probably also over-rely on the hopes that procurement practices can become best practices and thus disseminate themselves across the economy through some understanding of mimicking, or race to the top. This relates to discussions in other areas and to the broader expectation that procurement can be a trend setter and influence industry practice and standards. However, as the discussion on digitalisation will show, the direction of influence tends to be on reverse and there are very limited mechanisms to promote or force industry adaptation to procurement standards other than in relation to direct access to procurement.

IV. Procurement and the ‘Digital Transformation’ of the State

Another area of growing consensus is that public procurement has a key role to play in the ‘digital transformation’ of the State, as the process of digitalisation is bound to rely on the acquisition of technology from market providers to a large or sole extent (depending on each jurisdiction’s make or buy decisions). This can in turn facilitate the role of procurement as a tool of digital industrial policy, especially because procurement expenditure can be a way of ensuring demand for innovation, and because public sector technology adoption can be used as a domain for experimentation with new technologies and new forms of technology-enabled governance.

The European Union has set very high expectations in its Digital Agenda 2030, and the Commission has recently stressed that achieving them would require roughly doubling the predicted level of public procurement expenditure in digital technologies, and artificial intelligence (AI) in particular. It can thus be expected that the procurement of digital technologies will quickly gain practical importance even in jurisdictions that have been lagging so far.

However, echoing some of the issues concerning sustainable procurement, in this second stream of the ‘twin transition’, the uptake of procurement of digital technologies is slowed down by the complexity of procuring unregulated immature technologies, and the (digital) skills gaps in the public sector—which are exacerbated by the absence of a toolkit of regulatory and practical resources equivalent to that of green procurement. In such a context of technological fluidity and hype, given the skills and power imbalances between technology providers and public buyers, the shortcomings of the use of public procurement as a regulatory mechanism become stark and the flaws in the logic or expectation that procurement can be an effective tool of market steering are laid bare (Sanchez-Graells [2024]).

Public buyers are expected to act as responsible AI buyers and to ensure the ‘responsible use of AI’ in the public sector. The EU AI Act will soon establish specific requirements in that regard, although solely in relation to high-risk AI uses as defined therein. Implementing the requirements of the EU AI Act—and their extension to other types of uses of digital technology or algorithms as a matter of ‘best practice’—will leverage procurement processes and, in particular, the ensuing public contracts to impose the relevant obligations on technology providers. In that connection, the European Commission has promoted the development of model contractual AI clauses that seek to regulate the technology to be procured and their future use by the relevant public sector deployer.

However, an analysis of the model clauses and broader guidance on the procurement of AI shows that public buyers will still face a very steep knowledge gap as it will be difficult to set the detail of the relevant contracts, which will tend to be highly context dependent. In other words, the model clauses are not ‘plug and play’ and implementing meaningful safeguards in the procurement and use of AI and other digital technologies will require advanced digital skills and sufficient commercial leverage—which are not to be taken as a given. Crucially, all obligations under the model clauses (and the EU AI Act itself) hinge on (self-assessment) processes controlled by the technology provider and/or refer back to technical standards or the state-of-the-art, which are driven and heavily influenced (or entirely controlled) by the technology industry. Public buyers are at a significant disadvantage not only to set, but also to monitor compliance with relevant requirements.

This shows that, in the absence of mandatory requirements and binding (general) legislation, the use of procurement for regulatory purposes has a high risk of commercial determination and regulatory tunnelling as public buyers with limited skills and capabilities struggle to impose requirements on technology providers, and where references to standards also displace regulatory decision-making. This means that public procurement can no longer be expected to ‘monitor itself’, and that new forms of institutional oversight are required to ensure that the procurement of digital technologies works in the broader public interest.

V. Conclusion

Although the issues discussed above may seem rather disparate, they share a few common threads. First, in all areas, the regulatory use of procurement generates complexity and makes the day-to-day administration of procurement processes more complex. It can be hard for a public buyer to navigate socio-political, sustainability and digitalisation concerns—and these are only some of the ‘non-strictly procurement-related’ concerns and considerations to be taken into account. Such difficulty can be compounded by limited capabilities and by gaps in the required skills. While this is particularly clear in the digital context, the issue of limited (technical) capability is also highly relevant in relation to sustainable procurement. An imbalance in skills and commercial leverage between the public buyer and technology providers undermines the logic of using procurement as a regulatory tool. Implementation issues thus require much further thought and investment than they currently receive.

Ultimately, the effectiveness of the regulatory goals underpinning the leveraging of procurement hinges on the ability of public buyers to meaningfully implement them. This raises the further question whether all goals can be achieved at the same time, especially where there can be difficult trade-offs. And there can be many of those. For example, it can well be that the offeror of the most attractive technology comes from a ‘black-listed’ jurisdiction. It can also be that the most attractive technology is also the most polluting, or one that raises significant other risks or harms from a social perspective, etc. Navigating these risks and making the (implicit) political choices may be too taxing a task for public buyers, as well as raise issues of democratic accountability more generally. Moreover, enabling public buyers to deal with these issues and to exercise judgement and discretion reopens the door to risks of eg bias, capture or corruption, as well as maladministration and error, which are some of the core concerns in the narrow approach to the regulation of procurement as an administrative procedure to being with. Those trade-offs are also pervasive and hard to assess.

It is difficult to foresee the future, but my intuition is that the trend of piling up of regulatory goals on procurement’s shoulders will need to slow down or reverse if it is meant to remain operational, and that a return to a more paired down understanding of the role of procurement will need to be enabled by the emergence of (generally applicable) legislation and external oversight mechanisms that can discharge procurement of these regulatory roles. Or, at least, that is the way I would like to see the broader regulation and policymaking around procurement to evolve.

Bibliography

Andhov, Marta and Michal Andrzej Kania, ‘Restricting Freedom of Contract – the EU Foreign Subsidies Regulation and its Consequences for Public Procurement’ (2023) Journal of Public Procurement.

Arrowsmith, Sue, The Law of Public and Utilities Procurement. Regulation in the EU and the UK, vols 1 & 2 (3rd edn, Sweet & Maxwell 2014 and 2018).

Caranta, Roberto and Albert Sanchez-Graells (eds), European Public Procurement. Commentary on Directive 2014/24/EU (Edward Elgar 2021).

Georgopoulos, Aris, Bernard Hoekman and Petros C Mavroidis (eds), The Internationalization of Government Procurement Regulation (OUP 2017).

Halonen, Kirsi-Maria, ‘Is public procurement fit for reaching sustainability goals? A law and economics approach to green public procurement’ (2021) 28(4) Maastricht Journal of European and Comparative Law 535-555.

Janssen, Willem and Roberto Caranta (eds), Mandatory Sustainability Requirements in EU Public Procurement Law. Reflections on a Paradigm Shift (Hart 2023).

Sanchez-Graells, Albert, Public Procurement and the EU Competition rules (2nd end, Hart, 2015).

Sanchez-Graells, Albert, Digital Technologies and Public Procurement. Gatekeeping and Experimentation in Digital Public Governance (OUP 2024).

Steinicke, Michael and Peter L Vesterdorf (eds), Brussels Commentary on EU Public Procurement Law (C H Beck, Hart & Nomos 2018).

Some thoughts on the US' Executive Order on the Safe, Secure, and Trustworthy Development and Use of AI

On 30 October 2023, President Biden adopted the Executive Order on the Safe, Secure, and Trustworthy Development and Use of Artificial Intelligence (the ‘AI Executive Order’, see also its Factsheet). The use of AI by the US Federal Government is an important focus of the AI Executive Order. It will be subject to a new governance regime detailed in the Draft Policy on the use of AI in the Federal Government (the ‘Draft AI in Government Policy’, see also its Factsheet), which is open for comment until 5 December 2023. Here, I reflect on these documents from the perspective of AI procurement as a major plank of this governance reform.

Procurement in the AI Executive Order

Section 2 of the AI Executive Order formulates eight guiding principles and priorities in advancing and governing the development and use of AI. Section 2(g) refers to AI risk management, and states that

It is important to manage the risks from the Federal Government’s own use of AI and increase its internal capacity to regulate, govern, and support responsible use of AI to deliver better results for Americans. These efforts start with people, our Nation’s greatest asset. My Administration will take steps to attract, retain, and develop public service-oriented AI professionals, including from underserved communities, across disciplines — including technology, policy, managerial, procurement, regulatory, ethical, governance, and legal fields — and ease AI professionals’ path into the Federal Government to help harness and govern AI. The Federal Government will work to ensure that all members of its workforce receive adequate training to understand the benefits, risks, and limitations of AI for their job functions, and to modernize Federal Government information technology infrastructure, remove bureaucratic obstacles, and ensure that safe and rights-respecting AI is adopted, deployed, and used.

Section 10 then establishes specific measures to advance Federal Government use of AI. Section 10.1(b) details a set of governance reforms to be implemented in view of the Director of the Office of Management and Budget (OMB)’s guidance to strengthen the effective and appropriate use of AI, advance AI innovation, and manage risks from AI in the Federal Government. Section 10.1(b) includes the following (emphases added):

The Director of OMB’s guidance shall specify, to the extent appropriate and consistent with applicable law:

(i) the requirement to designate at each agency within 60 days of the issuance of the guidance a Chief Artificial Intelligence Officer who shall hold primary responsibility in their agency, in coordination with other responsible officials, for coordinating their agency’s use of AI, promoting AI innovation in their agency, managing risks from their agency’s use of AI …;

(ii) the Chief Artificial Intelligence Officers’ roles, responsibilities, seniority, position, and reporting structures;

(iii) for [covered] agencies […], the creation of internal Artificial Intelligence Governance Boards, or other appropriate mechanisms, at each agency within 60 days of the issuance of the guidance to coordinate and govern AI issues through relevant senior leaders from across the agency;

(iv) required minimum risk-management practices for Government uses of AI that impact people’s rights or safety, including, where appropriate, the following practices derived from OSTP’s Blueprint for an AI Bill of Rights and the NIST AI Risk Management Framework: conducting public consultation; assessing data quality; assessing and mitigating disparate impacts and algorithmic discrimination; providing notice of the use of AI; continuously monitoring and evaluating deployed AI; and granting human consideration and remedies for adverse decisions made using AI;

(v) specific Federal Government uses of AI that are presumed by default to impact rights or safety;

(vi) recommendations to agencies to reduce barriers to the responsible use of AI, including barriers related to information technology infrastructure, data, workforce, budgetary restrictions, and cybersecurity processes;

(vii) requirements that [covered] agencies […] develop AI strategies and pursue high-impact AI use cases;

(viii) in consultation with the Secretary of Commerce, the Secretary of Homeland Security, and the heads of other appropriate agencies as determined by the Director of OMB, recommendations to agencies regarding:

(A) external testing for AI, including AI red-teaming for generative AI, to be developed in coordination with the Cybersecurity and Infrastructure Security Agency;

(B) testing and safeguards against discriminatory, misleading, inflammatory, unsafe, or deceptive outputs, as well as against producing child sexual abuse material and against producing non-consensual intimate imagery of real individuals (including intimate digital depictions of the body or body parts of an identifiable individual), for generative AI;

(C) reasonable steps to watermark or otherwise label output from generative AI;

(D) application of the mandatory minimum risk-management practices defined under subsection 10.1(b)(iv) of this section to procured AI;

(E) independent evaluation of vendors’ claims concerning both the effectiveness and risk mitigation of their AI offerings;

(F) documentation and oversight of procured AI;

(G) maximizing the value to agencies when relying on contractors to use and enrich Federal Government data for the purposes of AI development and operation;

(H) provision of incentives for the continuous improvement of procured AI; and

(I) training on AI in accordance with the principles set out in this order and in other references related to AI listed herein; and

(ix) requirements for public reporting on compliance with this guidance.

Section 10.1(b) of the AI Executive Order establishes two sets or types of requirements.

First, there are internal governance requirements and these revolve around the appointment of Chief Artificial Intelligence Officers (CAIOs), AI Governance Boards, their roles, and support structures. This set of requirements seeks to strengthen the ability of Federal Agencies to understand AI and to provide effective safeguards in its governmental use. The crucial set of substantive protections from this internal perspective derives from the required minimum risk-management practices for Government uses of AI, which is directly placed under the responsibility of the relevant CAIO.

Second, there are external (or relational) governance requirements that revolve around the agency’s ability to control and challenge tech providers. This involves the transfer (back to back) of minimum risk-management practices to AI contractors, but also includes commercial considerations. The tone of the Executive Order indicates that this set of requirements is meant to neutralise risks of commercial capture and commercial determination by imposing oversight and external verification. From an AI procurement governance perspective, the requirements in Section 10.1(b)(viii) are particularly relevant. As some of those requirements will need further development with a view to their operationalisation, Section 10.1(d)(ii) of the AI Executive Order requires the Director of OMB to develop an initial means to ensure that agency contracts for the acquisition of AI systems and services align with its Section 10.1(b) guidance.

Procurement in the Draft AI in Government Policy

The guidance required by Section 10.1(b) of the AI Executive Order has been formulated in the Draft AI in Government Policy, which offers more detail on the relevant governance mechanisms and the requirements for AI procurement. Section 5 on managing risks from the use of AI is particularly relevant from an AI procurement perspective. While Section 5(d) refers explicitly to managing risks in AI procurement, given that the primary substantive obligations will arise from the need to comply with the required minimum risk-management practices for Government uses of AI, this specific guidance needs to be read in the broader context of AI risk-management within Section 5 of the Draft AI in Government Policy.

Scope

The Draft AI in Government Policy relies on a tiered approach to AI risk by imposing specific obligations in relation to safety-impacting and rights-impacting AI only. This is an important element of the policy because these two categories are defined (in Section 6) and in principle will cover pre-established lists of AI use, based on a set of presumptions (Section 5(b)(i) and (ii)). However, CAIOs will be able to waive the application of minimum requirements for specific AI uses where, ‘based upon a system-specific risk assessment, [it is shown] that fulfilling the requirement would increase risks to safety or rights overall or would create an unacceptable impediment to critical agency operations‘ (Section 5(c)(iii)). Therefore, these are not closed lists and the specific scope of coverage of the policy will vary with such determinations. There are also some exclusions from minimum requirements where the AI is used for narrow purposes (Section 5(c)(i))—notably the ‘Evaluation of a potential vendor, commercial capability, or freely available AI capability that is not otherwise used in agency operations, solely for the purpose of making a procurement or acquisition decision’; AI evaluation in the context of regulatory enforcement, law enforcement or national security action; or research and development.

This scope of the policy may be under-inclusive, or generate risks of under-inclusiveness at the boundary, in two respects. First, the way AI is defined for the purposes of the Draft AI in Government Policy, excludes ‘robotic process automation or other systems whose behavior is defined only by human-defined rules or that learn solely by repeating an observed practice exactly as it was conducted’ (Section 6). This could be under-inclusive to the extent that the minimum risk-management practices for Government uses of AI create requirements that are not otherwise applicable to Government use of (non-AI) algorithms. There is a commonality of risks (eg discrimination, data governance risks) that would be better managed if there was a joined up approach. Moreover, developing minimum practices in relation to those means of automation would serve to develop institutional capability that could then support the adoption of AI as defined in the policy. Second, the variability in coverage stemming from consideration of ‘unacceptable impediments to critical agency operations‘ opens the door to potentially problematic waivers. While these are subject to disclosure and notification to OMB, it is not entirely clear on what grounds OMB could challenge those waivers. This is thus an area where the guidance may require further development.

extensions and waivers

In relation to covered safety-impacting or rights-impacting AI (as above), Section 5(a)(i) establishes the important principle that US Federal Government agencies have until 1 August 2024 to implement the minimum practices in Section 5(c), ‘or else stop using any AI that is not compliant with the minimum practices’. This type of sunset clause concerning the currently implicit authorisation for the use of AI is a potentially powerful mechanism. However, the Draft also establishes that such obligation to discontinue non-compliant AI use must be ‘consistent with the details and caveats in that section [5(c)]’, which includes the possibility, until 1 August 2024, for agencies to

request from OMB an extension of limited and defined duration for a particular use of AI that cannot feasibly meet the minimum requirements in this section by that date. The request must be accompanied by a detailed justification for why the agency cannot achieve compliance for the use case in question and what practices the agency has in place to mitigate the risks from noncompliance, as well as a plan for how the agency will come to implement the full set of required minimum practices from this section.

Again, the guidance does not detail on what grounds OMB would grant those extensions or how long they would be for. There is a clear interaction between the extension and waiver mechanism. For example, an agency that saw its request for an extension declined could try to waive that particular AI use—or agencies could simply try to waive AI uses rather than applying for extensions, as the requirements for a waiver seem to be rather different (and potentially less demanding) than those applicable to a waiver. In that regard, it seems that waiver determinations are ‘all or nothing’, whereas the system could be more flexible (and protective) if waiver decisions not only needed to explain why meeting the minimum requirements would generate the heightened overall risks or pose such ‘unacceptable impediments to critical agency operations‘, but also had to meet the lower burden of mitigation currently expected in extension applications, concerning detailed justification for what practices the agency has in place to mitigate the risks from noncompliance where they can be partly mitigated. In other words, it would be preferable to have a more continuous spectrum of mitigation measures in the context of waivers as well.

general minimum practices

Both in relation to safety- and rights-impact AI uses, the Draft AI in Government Policy would require agencies to engage in risk management both before and while using AI.

Preventative measures include:

  • completing an AI Impact Assessment documenting the intended purpose of the AI and its expected benefit, the potential risks of using AI, and and analysis of the quality and appropriateness of the relevant data;

  • testing the AI for performance in a real-world context—that is, testing under conditions that ‘mirror as closely as possible the conditions in which the AI will be deployed’; and

  • independently evaluate the AI, with the particularly important requirement that ‘The independent reviewing authority must not have been directly involved in the system’s development.’ In my view, it would also be important for the independent reviewing authority not to be involved in the future use of the AI, as its (future) operational interest could also be a source of bias in the testing process and the analysis of its results.

In-use measures include:

  • conducting ongoing monitoring and establish thresholds for periodic human review, with a focus on monitoring ‘degradation to the AI’s functionality and to detect changes in the AI’s impact on rights or safety’—‘human review, including renewed testing for performance of the AI in a real-world context, must be conducted at least annually, and after significant modifications to the AI or to the conditions or context in which the AI is used’;

  • mitigating emerging risks to rights and safety—crucially, ‘Where the AI’s risks to rights or safety exceed an acceptable level and where mitigation is not practicable, agencies must stop using the affected AI as soon as is practicable’. In that regard, the draft indicates that ‘Agencies are responsible for determining how to safely decommission AI that was already in use at the time of this memorandum’s release without significant disruptions to essential government functions’, but it would seem that this is also a process that would benefit from close oversight by OMB as it would otherwise jeopardise the effectiveness of the extension and waiver mechanisms discussed above—in which case additional detail in the guidance would be required;

  • ensuring adequate human training and assessment;

  • providing appropriate human consideration as part of decisions that pose a high risk to rights or safety; and

  • providing public notice and plain-language documentation through the AI use case inventory—however, this is subject a large number of caveats (notice must be ‘consistent with applicable law and governmentwide guidance, including those concerning protection of privacy and of sensitive law enforcement, national security, and other protected information’) and more detailed guidance on how to assess these issues would be welcome (if it exists, a cross-reference in the draft policy would be helpful).

additional minimum practices for rights-impacting ai

In relation to rights-affecting AI only, the Draft AI in Government Policy would require agencies to take additional measures.

Preventative measures include:

  • take steps to ensure that the AI will advance equity, dignity, and fairness—including proactively identifying and removing factors contributing to algorithmic discrimination or bias; assessing and mitigating disparate impacts; and using representative data; and

  • consult and incorporate feedback from affected groups.

In-use measures include:

  • conducting ongoing monitoring and mitigation for AI-enabled discrimination;

  • notifying negatively affected individuals—this is an area where the draft guidance is rather woolly, as it also includes a set of complex caveats, as individual notice that ‘AI meaningfully influences the outcome of decisions specifically concerning them, such as the denial of benefits’ must only be given ‘[w]here practicable and consistent with applicable law and governmentwide guidance’. Moreover, the draft only indicates that ‘Agencies are also strongly encouraged to provide explanations for such decisions and actions’, but not required to. In my view, this tackles two of the most important implications for individuals in Government use of AI: the possibility to understand why decisions are made (reason giving duties) and the burden of challenging automated decisions, which is increased if there is a lack of transparency on the automation. Therefore, on this point, the guidance seems too tepid—especially bearing in mind that this requirement only applies to ‘AI whose output serves as a basis for decision or action that has a legal, material, or similarly significant effect on an individual’s’ civil rights, civil liberties, or privacy; equal opportunities; or access to critical resources or services. In these cases, it seems clear that notice and explainability requirements need to go further.

  • maintaining human consideration and remedy processes—including ‘potential remedy to the use of the AI by a fallback and escalation system in the event that an impacted individual would like to appeal or contest the AI’s negative impacts on them. In developing appropriate remedies, agencies should follow OMB guidance on calculating administrative burden and the remedy process should not place unnecessary burden on the impacted individual. When law or governmentwide guidance precludes disclosure of the use of AI or an opportunity for an individual appeal, agencies must create appropriate mechanisms for human oversight of rights-impacting AI’. This is another crucial area concerning rights not to be subjected to fully-automated decision-making where there is no meaningful remedy. This is also an area of the guidance that requires more detail, especially as to what is the adequate balance of burdens where eg the agency can automate the undoing of negative effects on individuals identified as a result of challenges by other individuals or in the context of the broader monitoring of the functioning and effects of the rights-impacting AI. In my view, this would be an opportunity to mandate automation of remediation in a meaningful way.

  • maintaining options to opt-out where practicable.

procurement related practices

In addition to the need for agencies to be able to meet the above requirements in relation to procured AI—which will in itself create the need to cascade some of the requirements down to contractors, and which will be the object of future guidance on how to ensure that AI contracts align with the requirements—the Draft AI in Government Policy also requires that agencies procuring AI manage risks by:

  • aligning to National Values and Law by ensuring ‘that procured AI exhibits due respect for our Nation’s values, is consistent with the Constitution, and complies with all other applicable laws, regulations, and policies, including those addressing privacy, confidentiality, copyright, human and civil rights, and civil liberties’;

  • taking ‘steps to ensure transparency and adequate performance for their procured AI, including by: obtaining adequate documentation of procured AI, such as through the use of model, data, and system cards; regularly evaluating AI-performance claims made by Federal contractors, including in the particular environment where the agency expects to deploy the capability; and considering contracting provisions that incentivize the continuous improvement of procured AI’;

  • taking ‘appropriate steps to ensure that Federal AI procurement practices promote opportunities for competition among contractors and do not improperly entrench incumbents. Such steps may include promoting interoperability and ensuring that vendors do not inappropriately favor their own products at the expense of competitors’ offering’;

  • maximizing the value of data for AI; and

  • responsibly procuring Generative AI.

These high level requirements are well targeted and compliance with them would go a long way to fostering ‘responsible AI procurement’ through adequate risk mitigation in ways that still allow the procurement mechanism to harness market forces to generate value for money.

However, operationalising these requirements will be complex and the further OMB guidance should be rather detailed and practical.

Final thoughts

In my view, the AI Executive Order and the Draft AI in Government Policy lay the foundations for a significant strengthening of the governance of AI procurement with a view to embedding safeguards in public sector AI use. A crucially important characteristic in the design of these governance mechanisms is that it imposes significant duties on the agencies seeking to procure and use the AI, and it explicitly seeks to address risks of commercial capture and commercial determination. Another crucially important characteristic is that, at least in principle, use of AI is made conditional on compliance with a rather comprehensive set of preventative and in-use risk mitigation measures. The general aspects of this governance approach thus offer a very valuable blueprint for other jurisdictions considering how to boost AI procurement governance.

However, as always, the devil is in the details. One of the crucial risks in this approach to AI governance concerns a lack of independence of the entities making the relevant assessments. In the Draft AI in Government Policy, there are some risks of under-inclusion and/or excessive waivers of compliance with the relevant requirements (both explicit and implicit, through protracted processes of decommissioning of non-compliant AI), as well as a risk that ‘practical considerations’ will push compliance with the risk mitigation requirements well past the (ambitious) 1 August 2024 deadline through long or rolling extensions.

To mitigate for this, the guidance should be much clearer on the role of OMB in extension, waiver and decommissioning decisions, as well as in relation to the specific criteria and limits that should form part of those decisions. Only by ensuring adequate OMB intervention can a system of governance that still does not entirely (organisationally) separate procurement, use and oversight decisions reach the levels of independent verification required not only to neutralise commercial determination, but also operational dependency and the ‘policy irresistibility’ of digital technologies.

European Commission wants to see more AI procurement. Ok, but priorities need reordering

The European Commission recently published its 2023 State of the Digital Decade report. One of its key takeaways is that the Commission recommends Member States to step up innovation procurement investments in digital sector.

The Commission has identified that ‘While the roll-out of digital public services is progressing steadily, investment in public procurement of innovative digital solutions (e.g. based on AI or big data) is insufficient and would need to increase substantially from EUR 188 billon to EUR 295 billon in order to reach full speed adoption of innovative digital solutions in public services’ (para 4.2, original emphasis).

The Commission has thus recommended that ‘Member States should step up investment and regulatory measures to develop and make available secure, sovereign and interoperable digital solutions for online public and government services’; and that ‘Member States should develop action plans in support of innovation procurement and step up efforts to increase public procurement investments in developing, testing and deploying innovative digital solutions’.

Tucked away in a different part of the report (which, frankly, has a rather odd structure), the Commission also recommends that ‘Member States should foster the availability of legal and technical support to procure and implement trustworthy and sovereign AI solutions across sectors.’

To my mind, the priorities for investment of public money need to be further clarified. Without a significant investment in an ambitious plan to quickly expand the public sector’s digital skills and capabilities, there can be no hope that increased procurement expenditure in digital technologies will bring adequate public sector digitalisation or foster the public interest more broadly.

Without a sophisticated public buyer that can adequately cut through the process of technological innovation, there is no hope that ‘throwing money at the problem’ will bring meaningful change. In my view, the focus and priority should be on upskilling the public sector before anything else—including ahead of the also recommended mobilisation of ‘public policies, including innovative procurement to foster the scaling up of start-ups, to facilitate the creation of spinoffs from universities and research centres, and to monitor progress in this area’ (para 3.2.3). Perhaps a substantial fraction of the 100+ billion EUR the Commission expects Member States to put into public sector digitalisation could go to building up the required capability… too much to ask?

"Can Procurement Be Used to Effectively Regulate AI?" [recording]

The recording and slides for yesterday’s webinar on ‘Can Procurement Be Used to Effectively Regulate AI?’ co-hosted by the University of Bristol Law School and the GW Law Government Procurement Programme are now available for catch up if you missed it.

I would like to thank once again Dean Jessica Tillipman (GW Law), Dr Aris Georgopoulos (Nottingham), Elizabeth "Liz" Chirico (Acquisition Innovation Lead at Office of the Deputy Assistant Secretary of the Army - Procurement) and Scott Simpson (Digital Transformation Lead, Department of Homeland Security Office of the Chief Procurement Officer - Procurement Innovation Lab) for really interesting discussion, and to all participants for their questions. Comments most welcome, as always.

ChatGPT in the Public Sector -- should it be banned?

In ‘ChatGPT in the Public Sector – overhyped or overlooked?’ (24 Apr 2023), the Analysis and Research Team (ART) of the General Secretariat of the Council of the European Union provides a useful and accessible explanation of how ChatGPT works, as well interesting analysis of the risks and pitfalls of rushing to embed generative artificial intelligence (GenAI), and large language models (LLMs) in particular, in the functioning of the public administration.

The analysis stresses the risks stemming from ‘inaccurate, biased, or nonsensical’ GenAI outputs and, in particular, that ‘the key principles of public administration such as accountability, transparency, impartiality, or reliability need to be considered thoroughly in the [GenAI] integration process’.

The paper provides a helpful introduction to how LLMs work and their technical limitations. It then maps potential uses in the public administration, assesses the potential impact of their use on the European principles of public sector administration, and then suggests some measures to mitigate the relevant risks.

This analysis is helpful but, in my view, it is already captured by the presumption that LLMs are here to stay and that what regulators can do is just try to minimise their potential negative impacts—which implies accepting that there will remain unaddressed impacts. By referring to general principles of public administration, rather than eg the right to good administration under the EU Charter of Fundamental Rights, the analysis is also unnecessarily lenient.

I find this type of discourse dangerous and troubling because it facilitates the adoption of digital technologies that cannot meet current legal requirements and guarantees of individual rights. This is clear from the paper itself, although the implications of part of the analysis are not sufficiently explored, in my view.

The paper has a final section where it explicitly recognises that, while some risks might be mitigated by technological advancements, other risks are of a more structural nature and cannot be fully corrected despite best efforts. The paper then lists a very worrying panoply of such structural issues (at 16):

  • ‘This is the case for detecting and removing biases in training data and model outputs. Efforts to sanitize datasets can even worsen biases’.

  • ‘Related to biases is the risk of a perpetuation of the status quo. LLMs mirror the values, habits and attitudes that are present in their training data, which does not leave much space for changing or underrepresented societal views. Relying on LLMs that have been trained with previously produced documents in a public administration severely limits the scope for improvement and innovation and risks leaving the public sector even less flexible than it is already perceived to be’.

  • ‘The ‘black box’ issue, where AI models arrive at conclusions or decisions without revealing the process of how they were reached is also primarily structural’.

  • ‘Regulating new technologies will remain a cat-and-mouse game. Acceleration risk (the emergence of a race to deploy new AI as quickly as possible at the expense of safety standards) is also an area of concern’.

  • ‘Finally […] a major structural risk lies in overreliance, which may be bolstered by rapid technological advances. This could lead to a lack of critical thinking skills needed to adequately assess and oversee the model’s output, especially amongst a younger generation entering a workforce where such models are already being used’.

In my view, beyond the paper’s suggestion that the way forward is to maintain human involvement to monitor the way LLMs (mal)function in the public sector, we should be discussing the imposition of a ban on the adoption of LLMs (and other digital technologies) by the public sector unless it can be positively proven that their deployment will not affect individual rights and more diffuse public interests, and that any residual risks are adequately mitigated.

The current state of affairs is unacceptable in that the lack of regulation allows for a quickly accelerating accumulation of digital deployments that generate risks to social and individual rights and goods. The need to reverse this situation underlies my proposal to permission the adoption of digital technologies by the public sector. Unless we take a robust approach to slowing down and carefully considering the implications of public sector digitalisation, we may be undermining public governance in ways that will be very difficult or impossible to undo. It is not too late, but it may be soon.

Source: https://www.thetimes.co.uk/article/how-we-...

"Tech fixes for procurement problems?" [Recording]

The recording and slides for yesterday’s webinar on ‘Tech fixes for procurement problems?’ co-hosted by the University of Bristol Law School and the GW Law Government Procurement Programme are now available for catch up if you missed it.

I would like to thank once again Dean Jessica Tillipman (GW Law), Professor Sope Williams (Stellenbosch), and Eliza Niewiadomska (EBRD) for really interesting discussion, and to all participants for their questions. Comments most welcome, as always.

Recording of webinar on 'Digitalization and AI decision-making in administrative law proceedings'

The Centre for Global Law and Innovation of the University of Bristol Law School and the Faculty of Law at Universidade Católica Portuguesa co-organised an online workshop to discuss emerging issues in digitalization and AI decision-making in administrative law proceedings. I had the great pleasure of chairing it and I think quite a few important issues for further discussion and research were identified. The speakers kindly agreed to share a recording of the session (available here), of which details follow:

Digitalization and AI decision-making in administrative law proceedings

This is a hot area of legal and policy development that has seen an acceleration in the context of the covid-19 pandemic. Emerging research finds points of friction in the simple transposition of administrative law and existing procedures to the AI context, as well as challenges and shortcomings in the judicial review of decisions supported (or delegated) to an AI.

While more and more attention is paid to the use of AI by the public sector, key regulatory proposals such as the European Commission’s Proposal for an Artificial Intelligence Act would largely leave this area to (self)regulation via codes of practice, with the exception of public assistance benefits and services. Self-regulation is also largely the approach taken by the UK in its Guide to using artificial intelligence in the public sector, and the UK courts seem reluctant to engage with the technology underpinning automated decision-making. It is thus arguable that a regulatory gap is increasingly visible and that new solutions and regulatory approaches are required.

The panellists in this workshop covered a range of topics concerning transparency, data protection, automation of decision-making, and judicial review. The panel included (in order of participation):

• Dr Marta Vaz Canavarro Portocarrero de Carvalho, Assistant Professor at the Faculty of Law of Universidade Católica Portuguesa, specialising in administrative law, and member of the Centro de Arbitragem Administrativa (Portuguese Administrative Law Arbitration Centre).

• Dr Filipa Calvão, President of the Comissão Nacional de Proteção de Dados (Portuguese Data Protection Authority) since 2012, and Associate Professor at the Faculty of Law of Universidade Católica Portuguesa.

• Dr Pedro Cerqueira Gomes, Assistant Professor at Universidade Católica Portuguesa and Lawyer at Cerqueira Gomes & Associados, RL, specialising in administrative law and public procurement, and author of EU Public Procurement and Innovation - the innovation partnership procedure and harmonization challenges (Edward Elgar 2021).

• Mr Kit Fotheringham, Teaching Associate and postgraduate research student at the University of Bristol Law School. His doctoral thesis is on administrative law, specifically relating to the use of algorithms, machine learning and other artificial intelligence technologies by public bodies in automated decision-making procedures.

Public procurement digitalisation: A step forward or two steps back? [guest post by Dr Kirsi-Maria Halonen]

In this guest post, Dr Kirsi-Maria Halonen offers some exploratory thoughts on the digitalisation of public procurement, its difficulties and some governance and competition implications. This post is based on the presentation she gave at a Finnish legal research seminar “Oikeustieteen päivät”, Aalto University, on 28-29 September 2019.

Digitalisation of procurement - background and goals

Digitalisation and e-procurement are considered to enhance the efficiency of the procurement process in the EU’s internal market. In line with the European Commission’s 2017 Procurement Strategy, procurement digitalisation can unlock better and faster transparency across the internal market, thus ensuring the possibility for economic operators to become aware of business opportunities, the facilitation of access to public tenders and the dissemination of information on the conditions of the award of public contracts.

Beyond mere transparency gains, procurement digitalisation is also expected to Increase the integrity of the awarding process and the public officials involved, thus fostering corruption prevention and good administrative practices. Finally, digitalisation is also expected to open new, more efficient monitoring possibilities both before and after contract execution, as well as the deployment of advanced big data analytics.

Directive 2014/24/EU and procurement digitalisation

Digitalisation and e-procurement are some of the main goals of Directive 2014/24/EU. Since October 2018, these rules impose the mandatory use of electronic communications throughout the whole public contract award procedure (eCommunication), the submission of tenders in electronic form (eSubmission) and created detailed rules for procedures meant solely for eProcurement, as well as simplified information exchange mechanisms (such as the ESPD) to facilitate electronic processing of procurement information.

Although the digital requirements in the Directive do not yet cover pre-award market consultations or post-award contracts and contract amendments, there are some trends to indicate that these may be the next areas of digitalisation of procurement.

State of the art at Member State level

Many Member States have taken digitalisation and transparency in public procurement even further than the requirements of Directive 2014/24/EU. Many contracting authorities use eProcurement systems for the management of the entire life-cycle of the tendering process. In Finland, there is now consolidated experience with not only an eProcurement system, but also with an open access Government spend database. Similarly, Portugal, Spain, Italy, Slovakia and Poland have also created open access contract registers for all public contracts and contract amendments.

Additionally, many Member States are committed to wider transparency outside the procurement procedures. For example, there is an emerging practice of publication of pre-tendering market consultation documents or audio/video meeting records. It is also increasingly common to provide open access to contract performance documents, such as bills, payments and performance acceptance (eg the UK national action plan on open contracting).

Concerns and opportunities in the digitalisation of procurement

Given the current trends of development of digital procurement, it is necessary to reflect not only on the opportunities that the roll-out of these technologies creates, but also some concerns that arise from increased transparency and the implications of this different mode of procurement governance. Below are some thoughts on four interrelated dimensions: corruption, SME participation, adoption of blockchain-base and algorithmic tools, and competition for public contracts.

Corruption

Public Procurement and other commercial relationships (eg real estate development) between public and private sector are most vulnerable to corruption (as repeatedly stressed by the OECD, Transparency International, Finnish National Bureau of Investigation, etc). In that regard, it seems clear that the digitalisation of procurement and the increased transparency it brings with it can prevent corruption and boost integrity. Companies across the EU become aware of the contract award, so there is less room for national arrangements and protectionism. Digitalisation can make tendering less bureaucratic, thus lessening the need and room for bribes. eProcurement can also prevent (improper) direct communication between the contracting authority and potential tenderers. Finally, the mere existence of electronic documentation makes it easier to track and request documents at a later stage: illegal purchases are not that easy to “hide”.

Yet, even after the roll-out of electronic documentation and contract registers, there will remain issues such as dealing with receipts or fabricating needs for additional purchases, which are recurring problems in many countries. Therefore, while digitalisation can reduce the scope and risk of corruption, it is no substitute for other checks and balances on the proper operation of the procurement function and the underlying expenditure of public funds.

SME participation

One of the goals of Directive 2014/24/EU was to foster procurement digitalisation to facilitate SME participation by making tendering less bureaucratic . However, tendering is still very bureaucratic. Sometimes it is difficult for economic operators to find the “right” contracts, as it requires experience not only in identifying, but also in interpreting contract notices. Moreover, the effects of digitalisation are still local due to language barriers – eg in Finland, tendering documents are mostly in Finnish.

Moreover, the uncertainty of winning and the need to put resources into tendering are the main reasons for not-bidding by SMEs (Jääskeläinen & Tukiainen, 2018); and this is not resolved by digital tools. On the contrary, and in a compounding manner, SMEs can be disadvantaged in eProcurement settings. SMEs rarely can compete in price, but the use of e-procurement systems "favours" the use of a price only criterion (in comparison to price-quality-ratio) as quality assessment requires manual assessment of tenders. The net effect of digitalisation on SME participation is thus less than clear cut.

Blockchain-based and algorithmic tools

The digitalisation of procurement creates new possibilities for the use of algorithms: it opens endless possibilities to implement algorithmic test for choosing “the best tender” and to automate the procurement of basic products and services; it allows for enhanced control of price adjustments in e-catalogues (which currently requires manual labor); and it can facilitate monitoring: eg finding signs for bid rigging, cartels or corruption. In the future, transparent algorithms could also attack corruption by minimizing or removing human participation from the course of the procurement procedure.

Digitalisation also creates possibilities for using blockchain: for example, to manage company records, official statements and documents, which can be made available to all contracting authorities across EU. However, this also creates risks linked to eg EU wide blacklists: a minor infringement in one Member State could lead to the economic operator’s incapability of participating in public tenders throughout the EU.

The implications of the adoption of both algorithmic and blockchain-based tools still requires further thought and analysis, and this is likely to remain a fertile area for practical experimentation and academic debate in the years to come.

Competition

Open public contract registers have become a part of public procurement regime in EU Member States where corruption is high or with a tradition of high levels of public sector transparency. The European Commission is pushing for their creation in all EU jurisdictions as part of its 2017 Procurement Strategy. These contract registers aim to enhance integrity of the procurement system and public official and to allow public scrutiny of public spending by citizens and media.

However, these registers can facilitate collusive agreements. Indeed, easier access to detailed tendering information facilitates monitoring existing cartels by its members: it provides means to make sure ”cartel discipline” is being followed. Moreover, it may facilitate the establishment of new cartels or lead to higher / not market-based pricing without specific collusive agreements.

Instead of creating large PDF-format databases of scanned public contracts, the European Commission indeed encourages Member States to create contract registers with workable datasets (user friendly, open, downloadable and machine-readable information on contracts and especially prices and parties of the contract). This creates huge risks of market failure and tendering with pricing that is not based on the market prices. It thus requires further thought.

Conclusions

Digitalisation has and is transforming public procurement regime and procedures. It is usually considered as a positive change: less bureaucracy, enhanced efficiency, better and faster communication and strengthening integrity of public sector. However, digitalisation keeps challenging the public procurement regime through eg automated processes and production of detailed data - leaving less room for qualitative assessments. One can wonder whether this contributes to the higher-level objectives of increasing SME participation and generating better value for money.

Digitalisation brings new tools for monitoring contracting authorities and to detect competition distortions and integrity failures. However, there is a clear risk in providing “too much” and “too detailed” pricing and contract information to the market operators – hence lowering the threshold of different collusive practices. It is thus necessary to reconsider current regulatory trends and to perhaps develop a more nuanced regulatory framework for the transparency of procurement information in a framework of digitalised governance.

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Guest blogger

Dr Kirsi-Maria Halonen is a Doctor of Laws and Adjunct Professor, Senior Lecturer in Commercial Law at University of Lapland. She is also a current Member of the European Commission’s Stakeholders Expert Group on Public Procurement (SEGPP, E02807), the Research Council at Swedish Competition Authority, the Finnish Ministry of Finance national PP strategy working group (previously also national general contract terms for PP (JYSE) working group), the Finnish Public Procurement Association, of which she is a board member and previous chair, and the European Procurement Law Group (EPLG).

In addition to public procurement law, Kirsi-Maria is interested in contract law, tort law, corruption and transparency matters as well as state aid rules. She is the author of several articles (both in English and in Finnish) and a few books (in Finnish). Most recently, she has co-edited Transparency in EU Procurements. Disclosure within Public Procurement and during Contract Execution, vol 9 European Procurement Law Series (Edward Elgar, 2019), together with Prof R Caranta and Prof A Sanchez-Graells.