Discussion
Started 25th Nov, 2023
  • UCD/VAWR

What steps should be taken to ensure fairness and inclusivity in AI development?

By incorporating these steps into the AI development process, developers and organizations can work towards creating AI systems that are not only technically proficient but also fair, transparent, and inclusive for diverse user groups. I would like to hear from you, please! Thanks!

Popular replies (1)

George Benneh Mensah
Africa Institute For Regulatory Affairs (AIFRA) LBG
Artificial Intelligence (AI) has become an integral part of our lives, from voice assistants to recommendation systems. However, as AI continues to advance, it is crucial that steps are taken to ensure fairness and inclusivity in its development. By incorporating these steps into the AI development process, developers and organizations can work towards creating AI systems that are not only technically proficient but also fair, transparent, and inclusive for diverse user groups.
Firstly, it is essential to have diverse teams working on AI development. A diverse team brings different perspectives and experiences to the table, which helps in identifying biases and ensuring a fair representation of all users. By including individuals from various backgrounds such as gender, race, ethnicity, age, and socioeconomic status in the development process, we can minimize the risk of biased algorithms that may discriminate against certain groups.
Secondly, transparency should be a fundamental principle in AI development. Developers must provide clear explanations for how their algorithms make decisions or recommendations. This transparency allows users to understand why they are receiving certain outcomes and helps identify any potential biases or unfairness in the system. Additionally, making the source code open-source or subjecting it to external audits can further enhance transparency and accountability.
Moreover, continuous monitoring and evaluation of AI systems are necessary to ensure fairness and inclusivity. Developers should regularly assess their algorithms for any unintended consequences or biases that may arise over time due to changing user behavior or data patterns. If biases are identified during this process, appropriate measures should be taken promptly to rectify them.
Furthermore, involving users in the design process can significantly contribute to fairness and inclusivity in AI development. User feedback should be actively sought throughout the entire development cycle – from initial design stages to post-deployment evaluations. This user-centered approach ensures that AI systems meet the needs of diverse user groups while avoiding discriminatory outcomes.
Lastly, collaboration between developers/organizations and regulatory bodies is crucial for establishing guidelines and regulations regarding fairness and inclusivity in AI development. By working together, they can create standards and frameworks that promote ethical practices and hold developers accountable for any biases or discriminatory outcomes.
In conclusion, ensuring fairness and inclusivity in AI development is of utmost importance. By incorporating diverse teams, promoting transparency, monitoring algorithms, involving users, and collaborating with regulatory bodies, developers and organizations can create AI systems that are not only technically proficient but also fair, transparent, and inclusive for all users. It is our responsibility to shape the future of AI in a way that benefits everyone while minimizing biases and discrimination.
8 Recommendations

All replies (3)

George Benneh Mensah
Africa Institute For Regulatory Affairs (AIFRA) LBG
Artificial Intelligence (AI) has become an integral part of our lives, from voice assistants to recommendation systems. However, as AI continues to advance, it is crucial that steps are taken to ensure fairness and inclusivity in its development. By incorporating these steps into the AI development process, developers and organizations can work towards creating AI systems that are not only technically proficient but also fair, transparent, and inclusive for diverse user groups.
Firstly, it is essential to have diverse teams working on AI development. A diverse team brings different perspectives and experiences to the table, which helps in identifying biases and ensuring a fair representation of all users. By including individuals from various backgrounds such as gender, race, ethnicity, age, and socioeconomic status in the development process, we can minimize the risk of biased algorithms that may discriminate against certain groups.
Secondly, transparency should be a fundamental principle in AI development. Developers must provide clear explanations for how their algorithms make decisions or recommendations. This transparency allows users to understand why they are receiving certain outcomes and helps identify any potential biases or unfairness in the system. Additionally, making the source code open-source or subjecting it to external audits can further enhance transparency and accountability.
Moreover, continuous monitoring and evaluation of AI systems are necessary to ensure fairness and inclusivity. Developers should regularly assess their algorithms for any unintended consequences or biases that may arise over time due to changing user behavior or data patterns. If biases are identified during this process, appropriate measures should be taken promptly to rectify them.
Furthermore, involving users in the design process can significantly contribute to fairness and inclusivity in AI development. User feedback should be actively sought throughout the entire development cycle – from initial design stages to post-deployment evaluations. This user-centered approach ensures that AI systems meet the needs of diverse user groups while avoiding discriminatory outcomes.
Lastly, collaboration between developers/organizations and regulatory bodies is crucial for establishing guidelines and regulations regarding fairness and inclusivity in AI development. By working together, they can create standards and frameworks that promote ethical practices and hold developers accountable for any biases or discriminatory outcomes.
In conclusion, ensuring fairness and inclusivity in AI development is of utmost importance. By incorporating diverse teams, promoting transparency, monitoring algorithms, involving users, and collaborating with regulatory bodies, developers and organizations can create AI systems that are not only technically proficient but also fair, transparent, and inclusive for all users. It is our responsibility to shape the future of AI in a way that benefits everyone while minimizing biases and discrimination.
8 Recommendations
Duong Pc
UCD/VAWR
1 Recommendation
George Benneh Mensah
Africa Institute For Regulatory Affairs (AIFRA) LBG
@Duong Dr. I'm most grateful!
4 Recommendations

Similar questions and discussions

Could a thinking generative artificial intelligence independently make decisions contrary to human expectations?
Discussion
6 replies
  • Dariusz ProkopowiczDariusz Prokopowicz
Could a thinking generative artificial intelligence independently make decisions contrary to human expectations which could lead to the annihilation of humanity?
Recently, the technology of generative artificial intelligence, which is taught certain activities, skills previously performed only by humans, has been developing rapidly. In the process of learning, artificial neural network technologies built on the likeness of human neurons are used, as well as deep learning technology. In this way, intelligent chatbots are created, which can converse with people in such a way that it can be increasingly difficult to diagnose, to distinguish whether we are talking to a human or an intelligent chatbot, a tool. Chatbots are taught to converse with the involvement of digital big data and information, and the process of conversation, including answering questions and executing specific commands is perfected through guided conversations. Besides, tools available on the Internet based on generative artificial intelligence are also able to create graphics, photos and videos according to given commands. Intelligent systems are also being created that specialize in solving specific tasks and are becoming more and more helpful to humans in solving increasingly complex problems. The number of new applications for specially created tools equipped with generative artificial intelligence is growing rapidly. However, on the other hand, there are not only positive aspects associated with the development of artificial intelligence. There are more and more examples of negative applications of artificial intelligence, through which, for example, fake news is created in social media, disinformation is generated on the Internet. There are emerging possibilities for the use of artificial intelligence in cybercrime and in deliberately shaping the general social awareness of Internet users on specific topics. In addition, for several decades there have been films in the genre of science fiction, in which futuristic visions of the future were presented, in which intelligent robots, equipped with artificial intelligence autonomous cyborgs (e.g. Terminator) or artificial intelligence systems managing the flight of a ship of an interplanetary manned mission (e.g. 2001 Space Odyssey), artificial intelligence systems and intelligent robots transformed humanity from a source of electricity to their needs (e.g. Matrix trilogy) and thus instead of helping people, they rebelled against humanity. This topic has become topical again. There are attempts to create autonomous human cyborgs equipped with artificial intelligence systems, robots able to converse with humans and carry out certain commands. Research work is being undertaken to create something that will imitate human consciousness, or what is referred to as artificial consciousness, as part of the improvement of generative artificial intelligence systems. There are many indications that humans are striving to create a thinking generative artificial intelligence. It cannot be ruled out that such a machine could independently make decisions contrary to human expectations which could lead to the annihilation of mankind. In view of the above, in the conditions of dynamic development of generative artificial intelligence technology, considerations about the potential dangers to humanity that may arise in the future from the development of generative artificial intelligence technology have once again returned to relevance.
In view of the above, I address the following question to the esteemed community of scientists and researchers:
Could a thinking generative artificial intelligence independently make decisions contrary to human expectations which could lead to the annihilation of humanity?
Could a thinking generative artificial intelligence independently make decisions contrary to human expectations?
And what is your opinion on this topic?
What is your opinion on this issue?
Please answer,
I invite everyone to join the discussion,
Thank you very much,
Best wishes,
Dariusz Prokopowicz
The above text is entirely my own work written by me on the basis of my research.
In writing this text I did not use other sources or automatic text generation systems.
Copyright by Dariusz Prokopowicz
The question is: Transplanting Consciousness?
Question
7 answers
  • Edward J TehovnikEdward J Tehovnik
Science fiction enthusiasts have often suggested that a time will come when one’s consciousness after death can be stored somewhere to continue its life, but obviously it takes more than storage to create life. Nevertheless, on storage, the current-day version of this is to write a book or create a piece of art with one’s name attached to it. If the work has a social impact, one will be guaranteed celebrity after death. One of my mentors, the late Professor Peter H. Schiller of MIT, used to mention in his lectures (to undergraduates) that the point of doing science is to become famous (whether in one’s lifetime or after death was never specified, but knowing Peter he would have preferred the former which typically requires getting a Nobel prize).
The ultimate neurophysiological engram is in the cerebellum, as mediated by the synapses onto the Purkinje neurons (Gallistel et al. 2022). The inputs to this circuit can be manipulated with direct electrical stimulation devoid of any telencephalon to create lasting memories in mammals, but the memories will lack the sensory/declarative richness provided by an intact neocortex (Tehovnik, Hasanbegović, Chen 2024). Since all conscious, declarative experience is stored in the telencephalon whose memory capacity in humans has been estimated to be 1.6 x 10^14 bits [or 2 ^(1.6 x 10^14) possibilities, Tehovnik, Hasanbegović, Chen 2024], this means it is conceivable that a telencephalon possessing the experience of another individual could be transplanted onto the cerebellar circuitry of someone who has undergone severe telencephalic damage. Two pieces of evidence support this idea. First, Stephen Hawking who had motor neuron disease (i.e., amyotrophic lateral sclerosis) could use a muscle twitch to deliver his lectures and contribute to scientific exchange since his telencephalon was intact so a computer could act as his cerebellum (De Lange 2011; Denman et al. 1997; Tehovnik, Patel, Tolias et al. 2021).
Second, a groundbreaking study was conducted by Prsa, Galiñanes et al. (2017). In this study electrical stimulation of the somatosensory cortex was used to condition individual neurons in the motor cortex using a ‘minimal’ brain-machine-interface paradigm. The only part of the preparation that was not under artificial control was the delivery of the reward, which could have been done by activation of the subcortical reward circuits of the forebrain (Olds and Milner 1954). This minimalist model proves that associations are made within the telencephalon at the single cell level, as—of course—already suspected by Hebb (1949, 1961, 1968). But unlike the minimalist circuit of the cerebellum (Gallistel et al. 2022), which under normal circumstances has access to the motor system via a rate code to drive the muscles, the telencephalon normally operates according to a conscious, declarative code given its massive innervation from all the senses and its enhancement of the sensory experience, as exemplified by the telencephalic visual system of primates containing neurons that encode color, motion, orientation, shape, texture, and depth (Schiller and Tehovnik 2015; Tehovnik, Hassanbegović, Chen 2024; Tehovnik, Patel, Tolias et al. 2021).
In short, we believe a time may come when a telencephalic module (representing all the conscious, declarative experiences of a lifetime) may be transplantable onto a subcortical cerebellar circuitry to continue one’s consciousness. However, the recovery of function will be imperfect: putting Pelé’s telencephalon onto Einstein’s cerebellum (and body) will not make for a world-class footballer; as well, we will learn at an instant the importance of all the subconscious motor routines stored in the donor’s cerebellum (and body). Sigmond Freud would have something to say about this.

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