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Nine recommendations for the governance of AI systems

Related concepts (22)

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Machine learning

Machine learning (ML) is an umbrella term for solving problems for which development of algorithms by human programmers would be cost-prohibitive, and instead the problems are solved by helping machines 'discover' their 'own' algorithms, without needing to be explicitly told what to do by any human-developed algorithms. Recently, generative artificial neural networks have been able to surpass results of many previous approaches.

Online machine learning

In computer science, online machine learning is a method of machine learning in which data becomes available in a sequential order and is used to update the best predictor for future data at each step, as opposed to batch learning techniques which generate the best predictor by learning on the entire training data set at once. Online learning is a common technique used in areas of machine learning where it is computationally infeasible to train over the entire dataset, requiring the need of out-of-core algorithms.

Corporate governance

Corporate governance are mechanisms, processes and relations by which corporations are controlled and operated ("governed"). "Corporate governance" may be defined, described or delineated in diverse ways, depending on the writer's purpose. Writers focused on a disciplinary interest or context (such as accounting, finance, law, or management) often adopt narrow definitions that appear purpose-specific. Writers concerned with regulatory policy in relation to corporate governance practices often use broader structural descriptions.

Automated machine learning

Automated machine learning (AutoML) is the process of automating the tasks of applying machine learning to real-world problems. AutoML potentially includes every stage from beginning with a raw dataset to building a machine learning model ready for deployment. AutoML was proposed as an artificial intelligence-based solution to the growing challenge of applying machine learning. The high degree of automation in AutoML aims to allow non-experts to make use of machine learning models and techniques without requiring them to become experts in machine learning.

Multistakeholder governance

Multistakeholder governance is a practice of governance that employs bringing multiple stakeholders together to participate in dialogue, decision making, and implementation of responses to jointly perceived problems. The principle behind such a structure is that if enough input is provided by multiple types of actors involved in a question, the eventual consensual decision gains more legitimacy, and can be more effectively implemented than a traditional state-based response.

Governance

Governance is the process of making and enforcing decisions within an organization or society. It is the process of interactions through the laws, social norms, power (social and political) or language as structured in communication of an organized society over a social system (family, social group, formal or informal organization, a territory under a jurisdiction or across territories). It is done by the government of a state, by a market, or by a network.

Supervised learning

Supervised learning (SL) is a paradigm in machine learning where input objects (for example, a vector of predictor variables) and a desired output value (also known as human-labeled supervisory signal) train a model. The training data is processed, building a function that maps new data on expected output values. An optimal scenario will allow for the algorithm to correctly determine output values for unseen instances. This requires the learning algorithm to generalize from the training data to unseen situations in a "reasonable" way (see inductive bias).

AI alignment

In the field of artificial intelligence (AI), AI alignment research aims to steer AI systems towards humans' intended goals, preferences, or ethical principles. An AI system is considered aligned if it advances the intended objectives. A misaligned AI system pursues some objectives, but not the intended ones. It can be challenging for AI designers to align an AI system because it can be difficult for them to specify the full range of desired and undesired behaviors.

Global governance

Global governance refers to institutions that coordinate the behavior of transnational actors, facilitate cooperation, resolve disputes, and alleviate collective action problems. Global governance broadly entails making, monitoring, and enforcing rules. Within global governance, a variety of types of actors – not just states – exercise power. Governance is thus broader than government. Global governance began in the mid-19th century. It became particularly prominent in the aftermath of World War I, and more so after the end of World War II.

General Data Protection Regulation

The General Data Protection Regulation (Regulation (EU) 2016/679, abbreviated GDPR) is a European Union regulation on Information privacy in the European Union (EU) and the European Economic Area (EEA). The GDPR is an important component of EU privacy law and human rights law, in particular Article 8(1) of the Charter of Fundamental Rights of the European Union. It also governs the transfer of personal data outside the EU and EEA.