Description: Humanistic AI refers to artificial intelligence systems designed with a focus on human values, ethics, and social good. This approach seeks to ensure that AI technologies are not only efficient and effective but also respect and promote human rights, equity, and social justice. Humanistic AI emphasizes the creation of algorithms and models that minimize bias and discrimination, ensuring that automated decisions are fair and transparent. Additionally, it promotes the inclusion of diverse perspectives in technology development, fostering dialogue among developers, users, and affected communities. This approach is crucial in a world where AI has an increasing impact on daily life, from healthcare to education and employment. Humanistic AI aims not only to improve the interaction between humans and machines but also to empower individuals, ensuring that technology serves the common good rather than particular interests. In summary, Humanistic AI represents a commitment to ethics and social responsibility in the development and implementation of artificial intelligence technologies.
History: The term ‘Humanistic AI’ began to gain relevance in the 2010s, in a context where the development of artificial intelligence raised ethical and social concerns. As AI became integrated into various fields, debates emerged about algorithmic bias and the lack of transparency in AI systems. In 2016, the Montreal Declaration for Responsible AI highlighted the importance of developing technologies that respect human rights and promote social well-being. Since then, various organizations and research groups have worked on creating ethical frameworks to guide AI development, emphasizing the need for a humanistic approach.
Uses: Humanistic AI is used in various applications, such as creating recommendation systems that avoid gender or racial biases, developing chatbots that respect user privacy, and implementing hiring algorithms that promote diversity. It is also applied in healthcare, where the aim is to ensure that automated diagnoses and treatments are fair and equitable, as well as in education, where tools are developed to support inclusive learning.
Examples: An example of Humanistic AI is the use of machine learning algorithms in job candidate selection, where measures are implemented to avoid racial and gender biases. Another case is the development of virtual assistants that prioritize user privacy and are designed to be accessible to people with disabilities. Additionally, some social media platforms are adopting Humanistic AI approaches to moderate content, seeking to balance freedom of expression with protection against hate speech.
