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Since the appearance of the global sustainable development goals (SDGs) in 2015, some sectors of the global communities were searching for the most optimal ways in their implementation: the academic community and researchers suggested theoretical background, while the corporate one proposed some practical solutions. Among the latter there are the so-called ESG, i.e. environmental, social and governance criteria providing for some new aspects in modern political economy. Some even suggest that artificial intelligence can help in finding proper criteria’s equilibrium.
Background
Environmental, social and governance, ESG aspects are gaining importance in both the general political economy and corporate spheres. Although the triangle follows most urgent global challenges (sustainability, climate mitigation and digitalisation), the ESG concept goes beyond “purely” environmental connotation: i.e. the emphasis is placed on social and governance issues. The need for a ESG-triangle’s approach to modern political economy is based on the following presumptions: environmental criteria explains the ways the corporate entities and numerous companies safeguard human environment; social criteria examine how companies and states are managing the relationships with employees, suppliers, customers and communities; and governance measures are aimed at available public/private instruments in regulating evolving basics in national political economy, including the role of political leadership, executive abilities, legislation, as well as audits, internal controls and shareholder rights.
Global and European challenges are fundamentally changing present political economy’s patterns in most of the states around the world. For example in the EU-27 the attention is towards some most vital aspects in EU-wide political economy’s transformations including such spheres as the “green deal”, competitiveness, digitalisation, renewable energy, etc.
More in: https://www.integrin.dk/2023/09/23/transformations-in-the-eus-political-economy-facing-modern-crises/
The global accounting
Clever minds in global management have quickly realised that the initial SDGs could be easily “commercialized” by introducing a rating system though slightly transformed: i.e. instead of original (and “abstract”) environmental, economic and social most profitable would be environmental, social and governance, the ESG.
Thus, in the financial sector, it is related to priority-investing in environment protection, social welfare and progressive corporate governance. Thus, the “general obligation” was formulated for all parts of national political economy’s facets: for example, the “big four” global accounting firms in ESG presently include: a) Deloitte, b) Ernst & Young, c) PricewaterhouseCoopers, PwC; d) and Klynveld Peat Marwick Goerdeler, KPMG. These companies provide auditing services, tax, strategy and management consulting, valuation, market research, assurance and legal advisory services; of course for a certain fee…
The ESG reporting frameworks is presently almost compulsory for use by companies for the disclosure of data covering business operations and opportunities and risks that are related to the environmental, social and governance aspects of their businesses.
One of the biggest problems with the ESG funds are those of combining the ESG ratings for corporate sectors, while creating a financial portfolio; presently, there is a lack of consensus regarding what the ESG ratings actually measure. ESG ratings can roughly be categorized as “impact based” or “risk based”.
Besides, there are the so-called “three Ps” referring to People, Planet, and Profit; thus sustainability has been dominating in protecting and maximising the benefit of the initial SDGs. These criteria are used by most states to assess corporate/organization’s impact in development going beyond traditional financial metrics. In their turn, the ESG represents a comprehensive approach that companies shall adopt to foster sustainable development and create business practices oriented to socially-accepted values.
There is a difference between the ESG and SDGs: the latter is a broader concept that encompasses environmental, social and economic considerations, whereas ESG specifically refers to a set of criteria within these three areas that are used to evaluate (by the rating system) the performance and behavior of companies.
Some differences between CSR and ESG are based on: a) the Corporate Social Responsibility, CSR refers to sustainability strategies businesses employ to ensure that the company is carried out ethically; b) whereas environmental, social and governance, ESG are criteria used to measure a company’s overall sustainability. In general, CSR refers to a company’s commitment to operating ethically and responsibly, considering its impact on society, the environment, and its stakeholders; the ESG takes this concept a step further, requiring integration into the company’s core purpose and supported by concrete evidence and data.
ESG: pros and cons
Being of recent origin, the ESG concept has been already getting some negative conations, specifically in financial and corporate spheres: a bad reputation in some corners of the business world. Advocates identify the problem with ESG as the excessive emphasis placed on the environment and not enough on corporate profitability. Some even argue that when used correctly, artificial intelligence may hold the answer to these problems, helping organisations emphasize all aspects of ESG in their projects.
It has to be underlined again that the term “ESG” (environmental, social and governance) is, actually, a replica of the UN-2030 Agenda’s sustainable development goals; the SDGs already in 2015 suggested a triple approach to SDGs’ implementation, i.e. through environmental, economic and social “means”.
More on the appropriate EU’s measures in sustainability in: https://www.integrin.dk/2023/12/20/eu-wide-plans-to-achieve-sustainability-updating-national-plans/
Several progressive steps already approved by the world community frameworks, like the mentioned UN SDGs and Paris clime agreement can serve both to identify some very positive sustainability and social objectives in existing generally non-sustainable growth patterns. It is known that most states’ political economies are being focused solely on increasing “total GDP” without due respect to environmental and nature protection issues, which are often lost in national SDG-assessment.
However, there are some positive signs: e.g. rating agency Morningstar issued a report showing that 2023 was the first year that ESG funds suffered a net outflow of capital: i.e. investors pulled more than US$13 billion out of sustainable funds due to concerns about underwhelming results, increasingly shrill political scrutiny and “the absence of clear, cross-border regulation for environmental, social and governance, and sustainable investing.” The agency is aware that the ESG risks include e.g. climate change impacts’ mitigation, environmental management practices, working condition, respect for human rights, anti-corruption practices, as well as compliance with the existing rule of law.
Source: https://dbrs.morningstar.com/esg
In corporate spheres, the ESG’s approach shall be concentrated on case-by-case basis and calculating “algorithmic models” for each ESG’s component. But most of the tools associated with green algorithms focus almost entirely on environmental impacts. Whether using an algorithmic calculator or performing manual data analysis, a more holistic and comprehensive approach is needed. In modern project management, well-defined social objectives can act as a roadmap, helping to guide the AI-driven solutions a company may employ.
Quite interesting are the recently suggested new strategic priorities for 2024-2029 in the “European Prosperity Plan”, which included the following growth elements: – making business easier and deepening the EU single market; – finalizing “clean industrial deal” with the member states to decarbonise and bring down energy prices; – putting research and innovation at the center of national political economy’s patterns, – boosting the EU-wide productivity with the “diffusion” of the digital technologies, including AIs; – massive investment in sustainable growth and competitiveness; and – tackling growing gaps in the skills and in labour markets. Couldn’t they be implanted into ESGs?
Source: https://commission.europa.eu/about-european-commission/president-elect-ursula-von-der-leyen_en
All ESG’s concerns explained above are real, although hardly taken seriously in most national growth patterns; quite often the obsession with environmental/ecological impacts tarnishes broader social, corporate and governance issues. Some argue that the “green blind spot” represents a significant and possibly existential threat to ESG; hence, without an equal emphasis on all three components in national progressive growth (environmental, social and governance) it is hard to believe that the states will come closer to more sustainable, clean and more resilient world order. There is hope, however, that artificial intelligence will assist in providing modern political economy with implementing ESGs; but under all circumstances, delivering on the ESG’s potentials would need a holistic approach to ensure that AI works in the positive direction.
More and reference to: https://blogs.lse.ac.uk/businessreview/2024/08/06/a-green-blind-spot-threatens-the-survival-of-esg-initiatives-ai-can-help/
Green algorithm’s calculation
As soon as the most vital ESG’s part is environmental, the “green transition” in the states takes additional attention. Thus, joint “green algorithm” project between Cambridge University and the University of Melbourne has underlined already in 2020 that it is possible to estimate the carbon footprint of national growth with a view to more environmentally friendly development. Presently accessible Green Algorithms Calculator has already been used in groundbreaking research into the carbon footprints of technology that requires massive computer power.
For example, a landmark study published in 2022 by Cambridge and the Baker Institute in Melbourne, Australia, found that the enormous energy needs of “large-scale computational infrastructure” required keen emphasis on using leading-edge software and hardware in data centers to avoid creating unsustainable and unjustifiable carbon emissions.
The study also found that some of the solutions being applied to date are making the problem worse. Some AI researchers were turning to “faster processors” to reduce running time and energy usage; though using “faster machines “can lead to greater carbon footprint”. Conversely, applying more efficient data centre software and hardware can reduce carbon footprints by more than 30 per cent, putting data mining and analysis on the right side of the ESG equation.
However, in their current form, these green algorithms – entirely focused on environmental impacts – do not necessarily help the ESG cause, nor ensure that urgently needed efforts to reduce greenhouse gas emissions would not have unintended negative consequences.
For corporate project managers, the real challenge is how to use AI to check all three ESG components: i.e. showing how to survive through a much longer period while using less energy, and providing society-wide benefits with a sufficient profitability.
For example, for projects in developing countries, donors and international agencies are attuned to using advanced, recycled and environmentally safe materials in construction (e.g. like bridges). However, these projects typically require materials to be imported, cutting local businesses out of procurement. Advanced materials also come with the need for workers with advanced skills who are not in ample supply in the recipient nation; bottom line: the needed work forces are imported damaging the local labour markets.
Before any algorithm can be integrated into the larger project management framework, it must be tested in real-world conditions. A well-executed pilot test provides insights into how well the algorithm serves the project’s sustainability and social goals and what fine-tuning may be needed. In this way the algorithm moves from a theoretical concept to a practical tool that helps the project meet its goals; so-to-say, gradually incorporating the algorithm into different aspects of the project while closely monitoring performance metrics. Some software platforms can “offer functionality” to track the implementation process across multiple departments or subprojects.
Fears that ESG is failing or has already failed are well founded: in the rush to claim ESG credentials, some experts are putting sole emphasis on environmental concerns to the detriment of social and governance.
The good news is that modern tools can provide developers with a complete insight and clarity about the full range of impacts of any project; it just has to be ensured that a wider view – and not only profitability’s temptation – should be focused on, and be satisfied not only by rating agencies.