AI as a technology equalizer

Extracted Attributes

• Core Concept

  Democratization of creative and technical abilities

• Economic Impact

  Predicted multi-trillion dollar AI infrastructure buildout

• Enabling Factors

  Widespread digital literacy and technology access

• Societal Challenge

  Potential to reinforce existing power structures and widen societal divides if not implemented thoughtfully

• Ethical Considerations

  Addressing biases in AI algorithms, ensuring transparency and accountability

• Philosophical Challenge

  Lack of 'intention' in AI-generated art leading to unsettledness

• Underlying Technologies

  AI algorithms, Natural Language Processing, Voice Recognition, Image Recognition, Sound Classification, AI chips, GPUs, CUDA platform

• Infrastructure Challenge

  Escalating energy consumption for AI, requiring massive new energy investments

• Primary Application Area

  Music (composition, production, marketing, consumption)

• Key Application (Accessibility)

  Improving digital accessibility for individuals with disabilities (e.g., hearing aids, image recognition)

Music and artificial intelligence

Music and artificial intelligence (music and AI) is the development of music software programs which use AI to generate music. As with applications in other fields, AI in music also simulates mental tasks. A prominent feature is the capability of an AI algorithm to learn based on past data, such as in computer accompaniment technology, wherein the AI is capable of listening to a human performer and performing accompaniment. Artificial intelligence also drives interactive composition technology, wherein a computer composes music in response to a live performance. There are other AI applications in music that cover not only music composition, production, and performance but also how music is marketed and consumed. Several music player programs have also been developed to use voice recognition and natural language processing technology for music voice control. Current research includes the application of AI in music composition, performance, theory and digital sound processing. Composers/artists like Jennifer Walshe or Holly Herndon have been exploring aspects of music AI for years in their performances and musical works. Another original approach of humans “imitating AI” can be found in the 43-hour sound installation String Quartet(s) by Georges Lentz (see interview with ChatGPT-4 on music and AI). 20th century art historian Erwin Panofsky proposed that in all art, there existed three levels of meaning: primary meaning, or the natural subject; secondary meaning, or the conventional subject; and tertiary meaning, the intrinsic content of the subject. AI music explores the foremost of these, creating music without the "intention" which is usually behind it, leaving composers who listen to machine-generated pieces feeling unsettled by the lack of apparent meaning.

Web Search Results

• AI as the Great Equalizer: Can Technology Bridge Social and ...

  Yet technology alone cannot guarantee more equitable outcomes. Without thoughtful implementation, community involvement, and policy support, AI could easily reinforce existing power structures and widen rather than bridge societal divides. The equalizing potential of AI ultimately depends less on the technology itself and more on the human values and choices that shape its development and deployment. [...] ##### Digital Literacy—The Missing Piece of the Puzzle The equalizing potential of AI depends on widespread digital literacy and technology access—the ability to use, understand, and critically evaluate digital tools. AI for social good fails if communities can’t meaningfully engage with the technology. True equity requires both access to technology and the skills to use it effectively. [...] Platforms like Ziki demonstrate this approach by adjusting difficulty levels in real-time based on student performance. Language barriers, too, fall under AI’s equalizing influence. Translation tools like Google Translate and Duolingo’s AI-powered language courses help immigrants and refugees access educational and professional opportunities previously closed to them.

• Bridging the Digital Divide with Artificial Intelligence - LTEN

  While AI has the potential to bridge the digital divide, it is crucial to ensure that AI technologies are developed and deployed ethically and inclusively. This involves addressing biases in AI algorithms that can lead to unequal outcomes and ensuring that AI systems are transparent and accountable. [...] The digital divide, which describes the disparity between those with access to modern information and communication technology and those without, continues to impede economic, educational and social progress globally. This divide is not just a technological issue but a significant barrier to economic, educational and social opportunities. [...] One concern is the potential for AI to exacerbate existing inequalities if not deployed thoughtfully. For instance, AI algorithms trained on biased data can perpetuate and even amplify discriminatory practices, leading to unequal access to opportunities and services. It is crucial to ensure that AI systems are transparent and accountable and that the underlying data used to train the model contains mechanisms to identify and mitigate bias.

• AI and Digital Accessibility Improve User Access | GrackleDocs

  In addition to transcription, AI is improving sound classification and enhancement technologies. For instance, hearing aids equipped with AI can distinguish between different types of noise and focus on amplifying human speech, making it easier for users to understand conversations in noisy environments. These smart hearing aids can also learn from user preferences and automatically adjust settings based on the environment. [...] AI technologies are revolutionizing accessibility for individuals with visual impairments through image recognition and descriptive audio. Image recognition software uses AI to analyze and describe visual content, converting images into detailed, context-aware audio descriptions. This enables visually impaired users to understand and interact with visual content on websites, apps, and social media. [...] AI involves creating systems that can perform tasks typically requiring human intelligence, such as visual perception, speech recognition, and decision-making. Machine learning, a subset of AI, involves training algorithms on large datasets to recognize patterns and make predictions or decisions without explicit programming for each task. These technologies are being applied to improve accessibility features in digital products, enabling more personalized and adaptive user experiences.

• AI in Higher Education: Bridging the Divide Between Access ...

  So, how can we address these challenges and ensure that AI doesn’t become a tool that deepens inequality? First, we need to ensure that AI is accessible to all students, regardless of their socio-economic background or geographical location. This means investing in infrastructure, particularly in areas where students currently have limited access to the necessary technology. Governments, institutions, and tech companies need to prioritise digital inclusion by providing affordable, reliable [...] particular, we must confront how access to AI tools may further entrench existing inequalities. [...] The issue of access is not just about whether students can get their hands on AI-powered devices, but whether they can engage with the technology in ways that genuinely enhance their learning. Students from lower-income backgrounds, those in rural areas, and those attending institutions with fewer resources are often at a disadvantage when it comes to access to the technology that powers AI tools. For these students, AI could become just another technological divide—reinforcing the gap between

• Digital accessibility in the era of artificial intelligence—Bibliometric ...

  Advancements in AI have created new opportunities to enhance digital accessibility for people with disabilities (Hapsari et al., 2017). However, as AI technology progresses, it is crucial to closely examine its impact on accessibility and to ensure that these technologies are developed in an equitable and inclusive manner. Despite the growing interest in the intersection of AI and digital accessibility, a comprehensive systematic review of the current state of knowledge and practices in this [...] Rapid advancements in technology have led to an increase in the use of digital devices for various purposes, including access to healthcare services. However, not everyone has equal access to these digital resources because of various barriers, such as physical, sensory, and cognitive disabilities. AI-powered technologies such as Automated Speech Recognition (ASR), Google Neural Machine Translation (GNMT), Google Vision API, and DeepMind are increasingly being used to improve accessibility for [...] Artificial intelligence (AI) is the capacity of a machine or computer system to simulate and perform tasks that typically require human intelligence, such as logical reasoning, learning, and problem resolution (Hassani et al., 2020). The determination of when applications and services can be classified as intelligent, as opposed to merely emulating intelligent behavior, is a topic of debate (Schank, 1991). Notwithstanding the ongoing philosophical discourse surrounding the extent and