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Building a case for decentralised AI ethics

  • Posted By
    10Pointer
  • Categories
    Science & Technology
  • Published
    1st Nov, 2021
Building a case for decentralised AI ethics

Introduction

  • AI ethics is a system of moral principles and techniques intended to inform the development and responsible use of artificial intelligence technology.
  • As AI has become integral to products and services, organizations are starting to develop AI codes of ethics.
  • An AI code of ethics, also called an AI value platform, is a policy statement that formally defines the role of artificial intelligence as it applies to the continued development of the human race.
  • The purpose of an AI code of ethics is to provide stakeholders with guidance when faced with an ethical decision regarding the use of artificial intelligence.

The rapid advancement of AI in the past few years has made it necessary to protect against the risk of AI to humans and develop decetralised AI ethics for effective utilization. This brief deals with important aspects of AI ethics and its decentralization.

Understanding the AI structure

  • Artificial intelligence (AI) is a wide-ranging branch of computer science concerned with building smart machines capable of performing tasks that typically require human intelligence.
  • In general, AI replicates actions that would have typically taken a human with a degree of expertise to perform.
  • With this, the intent of AI is almost always to achieve efficiency and effectiveness in terms of decision-making.
  • Examples of AI:
    • Siri, Alexa and other smart assistants
    • Self-driving cars
    • Robo-advisors
    • Conversational bots
    • Email spam filters
    • Netflix's recommendations

Artificial Intelligence History

1950s–1970s

Neural Networks

Early work with neural networks stirs excitement for “thinking machines.”

1980s–2010s

Machine Learning

Machine learning becomes popular.

Present Day

Deep Learning

Deep learning breakthroughs drive AI boom.

How far has AI come?

  • Artificial intelligence(AI) has already had a profound impact on business and society.
  • Applied AI and machine learning(ML) are creating safer workplaces, more accurate health diagnoses and better access to information for global citizens.
  • The Fourth Industrial Revolution will represent a new era of partnership between humans and AI, with potentially positive global impact.
  • AI advancements can help society solve problems of income inequality and food insecurity to create a more "inclusive, human-centred future" according to the World Economic Forum(WEF).

Why AI Ethics?

  • There is nearly limitless potential to AI innovation, which is both positive and frightening. 
  • Thus, there comes ‘AI Ethics’.
  • AI is susceptible to errors and bias when it's developed with malicious intent or trained with adversarial data inputs.
  • AI has enormous potential to be weaponised in ways which threaten public safety, security, and quality of life, which is whyAI ethics is so important.

What are the ethical dilemmas of artificial intelligence?

  • Automated decisions / AI bias
  • Autonomous things
  • Lethal Autonomous Weapons (LAWs)
  • Unemployment due to automation
  • Surveillance practices limiting privacy
  • Manipulation of human judgment
  • Proliferation of deepfakes
  • Inequality
  • Racist robots
  • Robot rights
  • Racism & Inequality
  • Security issues
  • Concerns regarding Robot rights

What is Decentralized AI?

  • Ethics in AI is essentially questioning, constantly investigating, and not taking for granted the technologies which are being rapidly imposed upon human life. 
  • Ethics is automatic: AI applies AI ethics to AI-intensive companies.
  • Decentralized Artificial intelligence is a model that allows for the isolation of processing without the downside of aggregate knowledge sharing.
  • By virtue, it enables the user to process information independently, among varying computing apparatuses or devices. 

How does it work? (Case Study)

Dentralised AI ethics works from the top down, from experts and their determinations down to users and their actions. An illustrative example emerged from the Frankfurt Big Data Lab in 2020.

  • A PhD-level team of philosophers, computer scientists, doctors, and lawyers united to approach AI-intensive startup companies in the field of medicine, and to collaboratively explore the ethical aspects of technological development.
  • The group’s work began with lengthy deliberations guided by AI ethics principles, and eventually concluded with case-study reports.
  • These reports have been published in academic journals, where they may be read by institutional lawyers and administrators, and eventually contribute to the promulgation of AI regulation by conventional means.
  • So, the process starts with high-level experts and works down to shape the user experience along a timeline of months and years.

Elements of Decentralized AI

  • Ground up: Instead of experts and high-level discussions, the process begins with common and public information. Companies routinely publish quarterly statements, which may include details about installed privacy protections, or efforts to ensure that their products work fairly across diverse populations.
  • Universal ethical evaluation: Instead of a boutique service offered at certain times to a select group of companies and products, evaluation of technological innovation occurs always and everywhere.
  • Implementation: Diverse users must be empowered to shape new technology through their own informed actions. Ideally, everyone should have access to the ethical insights generated by natural language processing and then be able to apply them on their own.

What is the need of decentralised AI?

  • The idea behind decentralised Artificial Intelligence (AI) ethics is simple: Instead of a single regulating authority, masses of individuals actively direct technologies through their own informed decisions and uses.
  • Countries can build robust frameworks to shape the trajectory of new AI technologies by empowering all users to participate.
  • Problems such as speed and innovation suffocation can be easily solved by decentralised AI ethics.
  • Decentralised finance provides an analogy: For cryptocurrency exchanges and smart-contract enforcement, it is users themselves who verify the transactions and legitimise or ostracise the practices and participants.
  • The difference is that where decentralised finance promotes economic growth, decentralised technological ethics facilitates human-centered AI innovation.

Potentail of Decentralized AI

  • Decentralized AI has incredible potential across businesses, science, and collective people.
  • Altogether, it will allow devices to overcome adversity through real-world challenges, by reasoning, and through trial and error, while having the results recorded.
  • Rather than slow methods of testing that traditional science has brought, there will be a priority towards speed with exponential points of testing.
  • Ideally, through several evolutions of life experiences through these challenges, the optimal results and total knowledge gained can be shared across devices.
  • Over the next ten years, devices that are learning through a decentralized AI network would benefit from those that have come before them and all of the other devices currently existing in the network.
  • They will be able to leverage, that domain knowledge gathered and convert that data into knowledge.
  • Through decentralized AI, people will have a definitive and continual structure in place that explains how things work.

Summing Up

Today, we are living in the innovating world but with innovation, there comes rocky roads before the path is laid out. The most important challenge is ‘ethical accuracy’. Unfortunately, this aspects is taken lightly which directly affect real people and society. Therefore, it is important for the world leader and stakeholders to work together in a collaborative mander to make innovation sustainble for all.

AI’s benefits stand to grow exponentially, but this can only happen if society trusts it. That’s why we believe AI systems must prioritize consumer privacy and data rights.