Issues related to AI
- The CEO of OpenAI, the company that makes ChatGPT, stated that the risks associated with AI are the “very subtle societal misalignments” that might cause the systems to cause chaos.
- Meritocracy’s development has undergone notable changes as a result of the criticisms and insights offered by scholars like Adrian Wooldridge, Michael Sandel, and Michael Young.
- By 2025, AI is expected to boost India’s GDP by $500 billion, or 10% of the goal amount.
- SUMMARY OF THE PROBLEM
Artificial intelligence (AI):
- It is a field of study in computer science that focuses on simulating intelligent computer behaviour.
- It depicts the process by which machines carry out actions that have traditionally required human intelligence.
- Machine learning, pattern recognition, big data, neural networks, self-algorithms, and other technologies are included.
- g: A few instances of AI that are currently present in our environment are Facebook’s facial recognition software, which recognises faces in the pictures we upload, and voice recognition software, which interprets our requests for Alexa.
Artificial Intelligence Generation:
- It is a state-of-the-art technological development that produces new types of media, including text, audio, video, and animation, by utilising artificial intelligence and machine learning.
- With the development of sophisticated machine learning skills, prompts—simple text—can now be used to create original, imaginative short- and long-form material, synthetic media, and even deep fakes.
Innovations in AI:
- Generative Adversarial Networks, or GANs
- Large Language Models, or LLMs
- Transformers that are Generatively Pre-trained.
- Creating Images for Experiments
- Make for sale products such as DALL-E to generate images.
- For text generation, use ChatGPT.
- It can compose marketing copy, computer code, blogs, and even search query results.
- People are not promoted or rewarded according to their social standing or upbringing, but rather according to their skills, accomplishments, and diligence.
Philosophers’ differing opinions about meritocracy:
- British scholar Young predicted in The Rise of the Meritocracy (1958) a dystopian meritocratic society.
- He imagined a world in which ability and hard work alone dictated social status and mobility in the year 2034.
- Measured by means of academic achievement and standardised testing.
- New tendency towards a merit-based system: This would bring about a different kind of social stratification.
Sandel’s criticism: emphasises the polarising effects:
- Meritocracy weakens social cohesiveness by encouraging a sense of entitlement among the successful and animosity among those who are left behind.
- Critical theorists, such as those from the Frankfurt School, critique meritocracy for concealing more complex power structures and disparities.
- Because meritocracy legitimises the elite’s standing under the pretext of impartiality and justice, it can sustain societal hierarchies.
- Post-structuralists cast doubt on the concept of merit, raising issues with definitions and standards of measurement.
- They contend that ideas about what constitutes excellence are socially created and represent the prejudices and interests of the powerful.
- Poststructuralism emphasises how merit is flexible and contingent.
- Meritocratic regimes have a subjective foundation and have the potential to worsen already-existing inequality.
Distinction between other models and Young’s dystopian meritocracy:
- Young’s concept produced a strict class system, and Sandel focused on the moral and social consequences of this.
- Wooldridge emphasises meritocracy’s capacity for reform as well as its actual progress.
- He examines in his book The Aristocracy of Talent how meritocracy—which at first was a driver for advancement and social mobility—
- It has become largely hereditary, with privileges being passed down through the generations, unintentionally creating new disparities.
- Wooldridge suggests changes, such as using selective schools as “escalators into the elite,” because she thinks they are inherently fair.
- promoting better technical education and expanding access for kids from disadvantaged backgrounds.
In what ways will artificial intelligence (AI) transform the concept of merit and meritocracy?
- AI introduces a non-human creature that is capable of carrying out activities and making judgements, calling into question the foundation of human value.
- Producing’ at a calibre that can beyond human capacity.
- When most jobs that were previously thought to require human intelligence and creativity are completed by robots, the traditional measures of merit lose some of their significance.
- Sora from OpenAI is proof that creativity is no longer a characteristic unique to humans.
- With AI, access to technology is prioritised over individual merit, which questions the idea of individual worth.
- Those who have access to AI technologies have a substantial edge, not because of their own skills but rather because of the improved capabilities of these tools.
- Biases in past data can be reinforced and even made worse by AI systems trained on that data.
- resulting in unfair practices in lending, recruiting, and law enforcement, among other domains.
- Already marginalised groups may be harmed by these biases.
- An AI technology can detect pancreatic cancer in a patient three years before radiologists can diagnose it, according to a recent article published in Nature Medicine.
- It may result in the replacement of jobs involving predictable, routine tasks.
- AI would affect high-paying positions.
- AI would compel workers into high-skill, high-paying positions.
- demanding intricate problem-solving and creativity, or low-skill, low-wage occupations that call for in-person communication and physical presence, which AI is still unable to imitate.
- Social inequality will worsen as a result of the polarisation, since those without access to advanced education and training will be forced into lower-paying jobs.
- Accountability is severely hampered by the opaque nature of many AI algorithms and the concentration of power within a small number of tech firms.
- The meritocratic ideal can be undermined by the opaque nature of many AI systems, which can make it difficult for people to know how to support or oppose judgements made by AI.
The Way Ahead:
- Data and the algorithms that process it are the foundation of artificial intelligence’s capabilities at the organisational level.
- Tech companies have a clear edge in developing more complex and precise AI models because they have access to previously unheard-of data volumes.
- These organisations have the power to define “merit” in the digital era, possibly excluding smaller competitors who could have creative ideas but require access to comparable datasets.
- Meritocracy must be reevaluated in light of AI developments, which calls for a complex knowledge of how society structures and technology interact.
- As AI tools have the potential to both enhance human talents and widen already existing disparities, it is imperative that we carefully reconsider how merit is determined and rewarded.
