This article discusses the main challenges of implementing artificial intelligence in government procurement and provides recommendations for addressing them. Institutional structures can leverage innovations in procurement by taking into account the specificities of artificial intelligence systems. Keywords: artificial intelligence, government services, machine learning, government institutions Government institutions around the world have a tremendous potential to harness the power of artificial intelligence (AI) to enhance government operations and citizen services. However, governments may lack experience in procuring advanced AI solutions and may exhibit caution in adopting new technologies. International organizations such as the World Economic Forum (WEF), along with companies like Deloitte and Splunk, have developed a set of steps for the utilization of AI in government procurement in their guide called "AI Procurement in a Box: AI Government Procurement Guidelines." This article will examine the key aspects recommended to countries for the integration of AI into their government procurement system. What is artificial intelligence? There is significant uncertainty regarding the nature of artificial intelligence (AI) systems and even what should be primarily considered as an algorithm. For example, a recent "algorithm" used by Stanford Medical School to allocate COVID vaccine doses essentially comprised a human-developed set of decision criteria rather than a complex system trained on available data. To discuss procurement-related issues, it is helpful to consider AI in a broader sense as "Automated Decision Systems" (ADS). These decision-making systems encompass "any systems, software, or processes that use computations to support or replace governmental decisions, judgments, and/or policy implementation that affect capabilities, access, freedoms, rights, and/or safety." The fact that these systems are increasingly being integrated into or even replacing governmental functions worldwide is crucial to understanding why they present significant challenges to current procurement processes. AI systems are typically optimized for specific goals, and the degree to which those goals align with their intended functions can vary significantly. They have the potential to improve the processes of governmental institutions and their interaction with citizens, such as using chatbots to facilitate communication and information retrieval. However, they also carry risks, such as when a facial recognition system used by the police mistakenly identifies an individual as a criminal, leading to their wrongful arrest. AI solutions that can be quickly implemented are often provided by private companies. As more and more aspects of government services are integrated into artificial intelligence systems and other privately-provided technologies, we observe a growing network of private infrastructure. As government agencies outsource critical technological infrastructures, such as data storage and cloud systems for data exchange and analysis, under the guise of modernizing public services, we see a trend of losing control over critical infrastructure and reducing accountability to the public that relies on it. Unlike private companies, which are accountable to their shareholders and driven by profit, government organizations are entrusted with considering the welfare of their entire population when providing solutions, and they are tasked with mitigating the harm caused by AI to the communities they serve. Two problems remain: The use of AI by the government is distinct. Governmental use of an algorithmic decision-making system entails different requirements than a product for private use. While it is expected that technology designed for public use will cater to the needs of all citizens, this is not necessarily the expectation for products created in private settings; in fact, many products are specifically tailored to a particular audience and then extended to a broader user base. This disconnect is often overlooked. Public use carries higher standards of compliance. Technologies designed for public use are subject to different requirements and legal criteria than the majority of privately-used technologies. "Government procurement" is one of the most heavily legislated and regulated areas of public administration. Typically, the activities related to government procurement are outlined in procurement guidelines provided by government entities and organizations. The absence of a clear procurement structure can complicate the development of accountability mechanisms that encompass all organizations. In the "AI and Procurement Primer" textbook by New York University, the authors identify six problems: The field of AI as a whole faces numerous terms that remain undefined. The first set of problems with definitions pertains to technologies and procedures: there is no consistent concept of AI or even an algorithm. This can hinder, for example, cataloging existing sociotechnical systems in government and hinder the development of procurement innovations specific to these technologies. Agencies and local authorities sometimes define these technologies for themselves, such as in registries or compliance reports, or as part of new regulations, but there is a lack of interagency coordination. Similarly, there are no agreed-upon definitions and procedures for assessing or auditing the impact of AI and its risks. The second set of problems with definitions relates to legal frameworks and principles, particularly fairness. There are vastly different understandings of what constitutes fairness in the context of AI. To arrive at a working definition of fairness that is truly fair, it is necessary to involve those who have suffered from AI's unfairness. The third set of problems with definitions pertains to metrics, especially success metrics, both for the AI system itself and the process by which it was acquired. There may be a lack of appropriate success metrics, or the success metrics may be contradictory. For example, fraud detection models measure success based on detecting anomalous behavior (e.g., abnormal for a human), which may indicate (but is not limited to) fraudulent behavior. Anyone whose credit card was frozen while on vacation would likely appreciate this distinction. These systems are not only used by banks; government institutions may also employ them to detect benefit fraud. While the technical definition of success may revolve around detecting as much fraud as possible, the practical definition of success may lie in detecting only those cases that are most likely to be fraud. Using the same methodologies, it will be possible to calculate potentially relevant companies and filter out those with a poor reputation and a high risk of misusing government procurement. The procurement process was designed to prevent abuses, but as a result, it contains reinforced sets of procedures that typically allow only large suppliers to meet the standards and compete for government contracts. Long-term contracts arising from these sets of procedures are entrenched within government institutions for many years and can create dependencies on the procedures. These dependencies can also extend to the emerging field of algorithmic auditing, where large suppliers who already have contracts with government institutions add algorithmic auditing to their portfolio of services, incentivizing government institutions to contract these services through their existing suppliers. Tensions in the procurement process also arise due to bottlenecks that can exist in procuring different services, such as when delays or distortions occur at various stages of procurement (particularly in the request for proposals, supplier selection, contract award, and execution). As the disproportionate impact of AI systems on individual citizens and communities becomes increasingly apparent, there is a pressing need to determine at what point in the procurement process risk and impact assessment should take place, importantly including the execution stage as well. Fig. 1. Procurement Activity Matrix As shown in the Procurement Activity Matrix, different types of tasks require varying levels of expertise and work volume. As the procurement process undergoes restructuring, it is necessary to identify points at which public participation and informed discussion can occur and be integrated. The incentives underlying both the procurement process as a whole and the various organizations involved in procurement can undermine the establishment of AI impact assessment structures. Sellers are driven by capitalist incentives and focus on generating profit by offering their services to government organizations. The primary responsibility of most suppliers lies with their shareholders, rather than with the clients or the people who use their services and systems. This means that current procedural and cultural procurement settings are supported by incentive structures that do not promote measures to protect the population or mitigate algorithmic harm, not least because they potentially slow down the procurement process. At this stage, the incentives of the government and the suppliers are effectively aligned: both are interested in quickly resolving the problem and transferring it through the contract once it is identified and budgets are approved. Both parties are also interested in presenting the technological solution as the most effective approach to any given problem. Government officials tasked with managing the procurement process may also lack an incentive to change the procurement process to account for potential AI technology harm. Their task is to procure as efficiently as possible, and there is no organizational or career reward for altering existing procedures. The institutional structure of government can pose challenges to innovations in procurement that consider the specificities of AI systems, especially when it comes to problem-solving timelines and implementing such innovations. According to former U.S. Chief Data Scientist DJ Patil, government policy is typically developed over a span of 10 years. Policies aim to exert influence during their (much shorter) tenure, often with the goal of re-election. The industry moves at an even faster pace. Policy and industry converge in speed when decision-makers are faced with the need to address problems within their jurisdiction, which may not necessarily align with government's organizational priorities and timelines. Another issue is that the "government" is often perceived as a monolithic entity, excluding alternative forms of governance from the discussion and, consequently, from innovation implementation efforts. Additionally, current procurement practices can undermine and erode infrastructural sovereignty. Procurement serves as a gateway for the adoption of technological infrastructure and, therefore, has long-term implications for cities, communities, and the agencies themselves. Due to limited capacity and/or resources to develop their own technologies, procurement entails the establishment of large-scale technological infrastructure, including AI, through private suppliers. This dynamic hinders transparency rather than promoting it: often protected by trade legislation, private suppliers are not obliged to open the "black box" and share information about their training data or models. Consequently, the promised outcome or narrative is often considered more important than the technological foundation. These promised outcomes and narratives often serve as a meeting point for agencies and the private sector, prioritized over establishing accountability in the procurement process, for example, in the context of climate emergencies and "clean technologies" or technologies deployed for public health management during the COVID-19 pandemic. AI systems implemented in such a manner that they can harm communities, for example, through excessive surveillance and policing, become infrastructural and are therefore unlikely to be dismantled, even if the harm is proven, such as in the case of smart sensors installed in streetlights. Increasing transparency and oversight in the procurement process (as opposed to focusing on technological prospects) can prevent the deployment of AI infrastructures that may be harmful by design. Agencies need resources to enhance literacy and expand capabilities regarding the consequences of acquiring AI systems, which includes knowledge sharing among agencies. The growing need to develop and ensure accountability structures in the context of procurement and deployment of AI systems by government institutions implies that these processes should be restructured to enable government agencies to understand the compromises and benefits of AI systems more quickly and confidently. Sufficient time should be allocated to identify and document the problem that the AI system should address and how it should address it. Affected communities must be heard. New legislation on artificial intelligence at both national and international levels (e.g., the EU's new AI regulation) should be effectively adopted and translated into changes in AI development, procurement, and usage. Working towards this process can create space for the development of the concept of collective accountability through AI procurement innovations, where government institutions, as buyers, can expand their authority by demanding accountability and transparency from suppliers and where agencies can revisit and iterate when issues arise. This new definition should serve as a reminder that political decisions are often encoded in the definition and construction of AI systems, and therefore, the procurement of these systems should consider nuances and account for other political definitions. Innovations in procurement are not possible without considering the legal implications, particularly those related to protecting purchasing organizations from liability. Government agencies often adhere to higher standards regarding their services and outcomes compared to private companies, and obligations are often seen as pure risks rather than an adaptive foundation for risk management. Furthermore, the influence of AI systems creates new complexities that challenge existing practices and accountability regimes. Currently, there are hardly any significant legislative safeguards to protect against the emerging discriminatory impacts of AI systems, such as human rights violations or anti-discrimination laws. Even when legal obligations concerning AI or other technologies apply to government institutions, these obligations are not necessarily taken into account by private companies when developing and testing technological products for use in the public sector. Instead, companies typically exploit spaces with limited citizen and government sector protections as a testing ground without accountability. Technologies tested in these liability-free spaces are then deployed by local agencies. Moreover, inherent uncertainty regarding the capabilities and functionalities (ex ante) and impact (ex post) of AI systems may require a reassessment of the distribution of obligations along AI supply chains. Direct contractors of government institutions may have multiple different suppliers, raising the question of who is responsible for the performance of the deployed AI system. Key measures that can help achieve greater clarity regarding the distribution of obligations along this AI supply chain include enhancing clarity in applicable contracts with suppliers (e.g., liability allocation, warranties, clarity on trade secret protection or incident insurance), thorough supplier vetting, post-deployment monitoring, and quality standards. The handbook also outlined a series of key actions for implementing AI in government procurement: Improving communication and understanding of AI systems, as well as the risks and harms they can pose, is essential. Procurement staff, policymakers, citizens, and suppliers need to have a better understanding of how specific instances of AI harm and risk are connected to larger structural issues, and vice versa. To create meaningful transparency, it is necessary to establish standards for reporting the goals and assumptions embedded in an AI system, as well as the risks and harms it may pose, along with recommendations for documenting and accounting for such reporting. There is a need for inter-agency communication and the exchange and building of capabilities in the procurement of AI systems. It is also necessary to clearly define intra-agency responsibilities for procuring AI systems and the impact they can have on citizens and the agencies themselves. Resources should be developed and shared to support individuals and communities within agencies working on improving procurement processes to mitigate harm from AI. Similarly, assistance should be provided to communities outside of agencies that are facing harm and issues related to AI. These resources and capacity-building opportunities should be interconnected in a network of procurement staff, AI researchers, advocacy representatives, and others. The realm of technologies that serve the public interest is expanding significantly. Government institutions are increasingly utilizing technologies, including artificial intelligence systems, in all aspects of their work. This means that there is a growing need for technologies that serve the public interest: professionals trained in both technical and social sciences who are capable of adequately assessing the social implications of constantly emerging technologies. Fortunately, among the next generation of technologists, there is also a growing desire to engage in meaningful work that considers the social impact of technology. Therefore, it is crucial that this talent is cultivated early and equitably. At the same time, both government institutions and the private sector need to focus on creating a range of job opportunities in the field of technologies that serve the public interest, hiring and retaining diverse talents at early stages of their careers, and supporting teams working on technologies that serve the public interest both within and beyond their organizations. Bibliography: AI Procurement in a Box: AI Government Procurement Guidelines. Sabine Gerdon, Eddan Katz, Emilie LeGrand, Gordon Morrison, Julián Torres Santeli World Economic Forum Guidelines 2020 AI and Procurement PRIMER Mona Sloane, Rumman Chowdhury, John C. Havens, Tomo Lazovich, Luis C. Rincon Alba 2021 For an up-to-date list of freedom of information laws around the world, see https://en.wikipedia.org/wiki/Freedom_of_information_laws_by_country (link as of 29.05.2020). Definition from the Engineering and Physical Science Research Council, a UK government research funding body. Абдыбеков, М.Д. Государственная закупка товаров, работ и услуг / М.Д. Абдыбеков, Н.А. Эшмамбетов. – Бишкек: 2000. Вульф, М. Потребности мира от глобальной торговой системы / М.Вульф. - Издательство Университета ООН, 2001. Джексон, Дж. Всемирная Торговая Организация: Конституция и Юриспруденция / Дж.Джексон. - Королевский Институт Международных дел, 1998. https://www.cnews.ru/news/line/2022-03-28_otechestvennyj_ii_uskorit https://www.coe.int/en/web/artificial-intelligence/ii-i-kontrol-koronavirusa-kovid-19

This article discusses the issues of improving legislation in the field of public procurement, the possibility of applying international experience. Among the significant changes that may affect the area of public procurement, one can note the simplification of procedures for conducting small purchases, support for the use of e-commerce tools, maintaining a common electronic database (archive) of current and completed purchases, and creating a statistical base for further analysis. Key words: public procurement, procurement plan, legislation. Introduction. The public procurement system is an integral part of the domestic trade sector for specific types of goods and services and serves as a mechanism for maintaining competition. The material and technical support for the implementation of government and municipal programs is one of the key factors contributing to the existence and gradual development of the public procurement system in the national economies of many countries. In the context of limited financial resources, countries pay increased attention to improving the legislative framework in the field of public procurement due to the fact that public procurement is one of the main directions of economic activity for any state. The legislative framework in the field of public procurement, regulating contractual relations between the public and private sectors, determines how the purchasing power of the state is realized in practice and is also intended to promote transparent and fair competition for obtaining government contracts. Thus, the quality of legislation on public procurement directly affects the quality of goods, works, or services delivered under government contracts and can significantly influence the volume of government expenditures. Outdated or ineffective legislation in the field of public procurement can lead to the wastage of limited budgetary resources and hinder fiscal reform implementation. Main Part. What is the work involved in government procurement? What are the main functions of public procurement? Ensuring compliance with and implementation of legislation on the contract system in the procurement of goods, works, and services to meet government needs, including the determination of suppliers (contractors, performers). Overall, as demonstrated by advanced international experience in the field of public procurement, it is necessary to eliminate factors that reduce efficiency and increase the costliness of the procurement process. However, we believe that ensuring a balance between the often competing principles of competitiveness, transparency, and efficiency should play a crucial role in the policy-making process in public procurement, taking into account the peculiarities of the local market, legal framework, and entrepreneurial culture. One of the most important factors that continue to influence the field of public procurement is the implementation of anti-corruption measures, particularly in countries with underdeveloped entrepreneurial culture. In relation to criteria based on advanced practices in developing public procurement models, they were subsequently transformed into indicators and evaluation criteria. The evaluation criteria are based on the idea that the primary function of legislation on public procurement is not to facilitate unhindered international trade or save public funds, but to establish minimum standards for procurement in the public sector. Legislation on public procurement regulates the processes of acquiring goods, performing works, and providing services for government clients. These processes are part of resource and budget management systems. The procurement process begins with the identification of the needs of government clients, followed by the development of a sourcing strategy, allocation of budgetary funds, and the implementation of tendering procedures, evaluation, and supplier selection. In the interest of a potentially significant number of end-users, after the contract is awarded, monitoring its execution is crucial. In public procurement rules, these processes are often reflected as three main stages: pre-tender stage, competitive bidding, and post-tender stage. In the case of government clients, the complex process of entering into commercial contracts must take into account the principles of the public sector, such as transparency in decision-making processes and accountability of the public sector to taxpayers, who are the ultimate beneficiaries of the goods provided under government contracts. The content of national legislation on public procurement depends on the goals of the government's procurement policy and the contractual and legal culture within a particular country. Fig. 1. Key Stages of the Public Procurement Process. Legislation in the field of public procurement should comply with international standards in order to uphold the principles of good governance. One of the main challenges in modeling the legal framework for public procurement is determining the extent to which advanced international experience is relevant to the socio-economic conditions of a particular country. For any state, the complexity lies in developing national legislation in the field of public procurement that adequately takes into account advanced international experience while also considering: (a) the specific characteristics of the local market (suppliers and contractors present in the market),/p> (b) the peculiarities of the country's business culture, (c) the level of development of communication technologies in the country. Additionally, the public procurement regulatory system should take into account the differences between government contracts funded from the state/municipal budget (classic government procurement) and contracts in the field of communal services (procurement in the communal sector). Normative gaps reflect how national legislation in the field of public procurement aligns with benchmark indicators. The greater the coverage of the legal regime of public procurement in a particular country, the smaller the normative gap will be. Therefore, the normative gap is calculated as the difference between the maximum value of a specific benchmark indicator and the scores given for the quality of national legislation in public procurement, including the institutional framework. The normative gap demonstrates the extent to which opportunities for improvement are identified through the evaluation of existing legislation in the country (the "law on paper"). Conclusions and Recommendations. The public procurement system, for example, in Russian practice is a relatively new tool in the relationship between the government and business, and it began to develop shortly after the transition to a market economy. However, public procurement in other countries has a longer history, organically shaped under the influence of historical, economic, political, and other factors. While the institution of public procurement in Russia is based on adapting foreign experience, the process of its organization in the original conditions presents scientific interest. Below are the main provisions of the formation of public procurement in the USA and Europe. Foreign experience. The greatest experience in this field has been accumulated in the USA, where the first law on public procurement was adopted in 1792 [1]. The total volume of procurement is divided into several parts, the main ones being procurement for the needs of federal authorities (with the responsible body being the General Services Administration), as well as procurement for the needs of national defense, where the responsible body is the US Department of Defense. It should be noted that the legislation and organization of the procurement process in the country underwent significant changes in 1994 when a complete revision of public procurement was carried out. Among the most significant changes, the following should be noted: a) Simplification of procedures for conducting small procurements with a value of less than 100,000 dollars, which facilitated the participation of small and medium-sized businesses. b) Support for the use of e-commerce tools (email, payment systems, etc.) and parallel facilitation of paper document flow. c) Support for maintaining a comprehensive electronic database (archive) of current and completed procurements, which has created a statistical foundation for subsequent analysis. The Federal Contracting System (FCS) in the United States is a crucial element of government regulation and planning, serving both economic functions (such as facilitating the government's connection with the market economy, stimulating scientific and technological development, and supporting military production) and social functions (such as advancing healthcare, education, and other social sectors). This system is built on the principle of professionalism of the contracting authority, represented by the Office of Federal Procurement, established in 1974. It is important to highlight the protectionist policy in the country regarding American manufacturers. According to the package of laws known as the "Buy American" Act, issued by the U.S. Congress in 1933, there was a prohibition on the use of any foreign goods to meet government needs, except in cases where they significantly surpassed domestic goods in terms of quality and cost. In the European Union countries, the system of public procurement is largely based on the American experience. Firstly, it is worth noting the division of organizational methods into two main types: centralized and decentralized procurement. In the case of centralized procurement, purchases for various departments and agencies are conducted by a single entity, which then resells the goods or services to specific government entities at wholesale prices, minus a small margin. The advantage of this approach is the ability to secure low prices due to the large-scale wholesale nature of the purchases. However, the drawback is the loss of flexibility and the ability to accommodate various nuances and specifications of individual departments. Centralized systems are present in countries such as Bulgaria, Cyprus, the Czech Republic, Estonia, Poland, and others. In the second case, each department independently conducts procurement for its own needs, usually through a specially organized department. In contrast to the centralized system, the advantage here is the flexibility in procuring goods and services with specific characteristics, while the disadvantage is the significant costs involved in maintaining procurement departments within each department. This system is used in Finland and Portugal. Finally, among most European countries (such as Austria, Germany, France, Italy, etc.), a popular approach is the combined structure, where there is a single entity responsible for coordinating, planning, and monitoring procurement, while each department directly carries out the procurement process. A unique feature of the European Union is the fact that access to a unified database of orders is available for certain countries. Alongside the obvious advantages of such organization, the protection of domestic suppliers becomes a significant concern. Therefore, in many countries, preferential treatment is granted to local producers. In conclusion, despite the influence of foreign countries' experience on the formation of the Federal Contract System (ФКС) in our country at the present stage, it is important to take into account both the historical development and, as mentioned earlier, the contractual and legal culture of each individual country, within which fundamental principles of the procurement institution were established. It is worth noting that "Every form of government, once established, contains within itself the material for its own improvement," which implies that young countries have the opportunity to distinguish inherent aspects in the search for research, improve, and keep pace with the times. Bibliography: Баранова, В.П. Экономика и организация научной и хозяйственной деятельности // Инноватика и экспертиза. – М.: 2015 Mortgages in transition economies, Европейский банк реконструкции и развития, Лондон, 2007. Доступное по адресу: www.ebrd.com/downloads/research/ guides/mit.pdf Журнал институциональных исследований Учредители: Humanitarian Perspectives Publishing House ISSN: 2076-6297eISSN: 2412-6039