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Five Keys to Understanding Artificial Intelligence


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Artificial intelligence (AI) is rapidly advancing, revolutionizing multiple sectors and promising significant benefits for society. Recognizing the need to address the development and use of AI comprehensively, the European Union (EU) is taking a leading role in regulating AI. The proposed Artificial Intelligence Act (AIA) aims to establish strict rules for AI in the EU, focusing on data quality, transparency, human oversight, and accountability.


The AIA introduces a classification system that prohibits AI systems posing unacceptable risks, regulates high-risk systems used in critical sectors, and imposes fewer requirements on systems with limited or minimal risk. Transparency and accountability are fundamental principles of the AIA. Developers and users of AI systems would be obliged to provide comprehensive information regarding system functionality and usage. Additionally, measures to mitigate AI-related risks, such as combating bias and discrimination, would be enforced.


The AIA is expected to be finalized in 2023, shaping the future of AI implementation and its impact on individuals and businesses at both the European and national level in Spain. In the present article, we will delve into the five keys to understanding artificial intelligence, shedding light on the implications of AI and its potential impact on various sectors.


Key 1: Understanding the Impact of AI in the Public Sector 

The first key to understanding AI lies in the public sector. It involves recognizing the need for comprehensive governance and evaluation frameworks. It is important to prioritize inclusive development and the restoration of trust between policymakers and the public. To achieve these goals, there’s a need for a deeper understanding of the benefits and risks associated with AI in the public sector. By comprehensively evaluating AI systems, policymakers can identify potential pitfalls, such as bias and discrimination, and take proactive measures to mitigate them. With strong evaluation frameworks in place, policymakers can make informed decisions and foster the responsible adoption of AI technologies.


To explore further on the subject and gain a deeper understanding of the perils and powers of AI in the public sector, refer to the full whitepaper “Governing algorithms. Perils and powers of AI in the public sector“. This document provides detailed insights into five AI use case studies from European countries and other international examples, proving the importance of responsible AI development, ethical purposes, and technical robustness in building trust and facilitating the uptake of AI. 


Key 2: Meaningful Human Oversight of Automated Decision-Making Systems 


The second key to understanding AI lies in recognizing the complexities and risks associated with automated decision-making systems (ADMS) and the importance of meaningful human oversight. While human oversight is often seen as a regulatory safeguard, experts caution against relying solely on human supervision, as the risks posed by ADMS extend beyond the discretion of frontline workers.


To effectively minimize the harms of bias and discrimination in decision-making, policymakers need a deep understanding of the risks and complexities of using ADMS. This understanding should encompass both the regulation of human-algorithm interaction and the study of human-computer interaction. By acknowledging the limitations of human oversight and engaging with the intricate nature of human-algorithm interactions, policymakers can develop more effective regulations and ensure meaningful human involvement in decision-making processes. 


To get informed more on this topic refer to the report “Towards a meaningful human oversight of automated decision-making systems“, that delves into the definition, regulation, and practice of human oversight, providing recommendations for policymakers and companies to navigate the challenges of ADMS and create meaningful human involvement in decision-making processes. 


Key 3: Addressing Algorithmic Discrimination and the Legal Framework 


The third key to understanding AI revolves around algorithmic discrimination and the legal framework. The use of AI applications has raised concerns regarding the potential for discriminatory outcomes resulting from automated decision-making systems. To effectively address algorithmic discrimination, it is crucial to define it and evaluate how it can be mitigated within the regulatory framework. 


The existing anti-discrimination mechanisms under the Spanish Constitution and law should be directly connected to the development of AI regulations. This connection ensures that discrimination is actively addressed and considered in the context of AI systems. However, one of the challenges in combating algorithmic discrimination lies in the opacity of AI systems and the decision-making logic employed by the companies that create and own them. 


To gain a more comprehensive understanding of algorithmic discrimination and its implications within the legal framework, refer to the report “Algorithmic discrimination in Spain: limits and potential of the legal framework.” This report analyzes the legal implications of AI systems and assesses whether Spain’s anti-discrimination and gender equality laws are capable of adequately addressing algorithmic discrimination. It also delves into the complexities surrounding the identification of algorithmic discrimination and the difficulties that may arise from differing perspectives among technologists, lawyers, and public policy analysts. 


Key 4: Applying AI to Climate Change Mitigation 


The fourth key to understanding AI lies in its potential to address the climate emergency. With the world needing to reduce greenhouse gas emissions and limit global warming, AI researchers and practitioners are leveraging the power of AI to tackle the complex challenges posed by climate change. The urgency of the situation provides an opportunity for countries like Spain to take a global lead in applying AI to climate change mitigation. 


Spain, with its solid reputation in climate change research and access to AI and machine learning expertise, is already fostering an environment conducive to AI-driven climate change projects. The country has seen success in pioneering Spanish projects that apply AI to address the climate crisis. The intersection of AI and climate change mitigation has the potential not only to benefit society but also to advance the field of machine learning itself. 


To explore further and gain insights into Spanish projects that are at the forefront of AI and climate change, refer to the full investigation “AI and Spain’s climate change and decarbonisation agenda“. This report presents case studies of Spanish projects working at the intersection of AI and climate change, demonstrating the diverse range of initiatives in Spain that are leveraging AI to mitigate the impacts of climate change. 


Key 5: Harnessing AI and Emerging Technologies for Sustainable Urban Development 


The fifth key to understanding AI involves harnessing emerging technologies to address urban challenges in the climate decade. As cities continue to grow and face increasing pressures on resources and the environment, innovative solutions are needed to achieve sustainability goals. Emerging technologies, including AI, machine learning, blockchain, big data, the Internet of Things (IoT), and 5G, offer transformative tools that can help cities tackle these challenges and contribute to the fulfillment of the Sustainable Development Goals (SDGs). 


With over half of the global population residing in urban areas, cities have a significant impact on natural resource consumption, waste generation, and greenhouse gas emissions. By leveraging emerging technologies, cities can optimize resource management, improve infrastructure, enhance transportation systems, and promote sustainable practices. These technologies enable cities to collect and analyze vast amounts of data, leading to better decision-making, increased efficiency, and the development of innovative solutions tailored to local contexts. The integration of AI and other emerging technologies in urban planning and governance can help create more sustainable and resilient cities. 


To delve deeper into the potential of emerging technologies in addressing urban challenges and their implications for sustainability and climate change, refer to the policy brief “Emerging technologies, a lever to tackle urban challenges in the climate decade: The case of Barcelona.” This report explores the role of emerging technologies in empowering cities, particularly focusing on Barcelona, to achieve their climate and sustainability objectives. It highlights how AI, along with other transformative technologies, can enable cities to become key agents in the fight against the climate emergency and the realization of the 2030 Agenda. 


Understanding artificial intelligence requires a multifaceted approach that encompasses various sectors and considerations. The keys discussed in this article highlight the importance of comprehensive governance frameworks in the public sector, meaningful human oversight of automated decision-making systems, addressing algorithmic discrimination within the legal framework, leveraging AI for climate change mitigation, and harnessing emerging technologies for sustainable urban development. With a comprehensive understanding of AI and its potential impact, we can shape a future where artificial intelligence benefits society while upholding ethical standards and protecting individuals’ rights.