Artificial intelligence (AI) is making our lives better in many ways, including through smartphones, household appliances, and self-driving automobiles. Artificial intelligence will affect every facet of our personal and professional lives. AI, or artificial intelligence, is computer software capable of mimicking human cognitive processes. As a result, AI is more efficient and accurate, especially when doing routine jobs. Sixty-three per cent of AI businesses surveyed by Global AI said that they saw an increase in revenue from using AI across their company. This was especially true for marketing and sales, product and service development, and supply chain management. Using complex machine learning models, for instance, Uber can anticipate when riders will be in a particular zone and dispatch cars accordingly.
While AI has many positive applications, it also poses some threats, such as when an IBM subsidiary secretly gathered user information from its weather app and sold it to marketers. UnitedHealth, in the USA, gave preference to white patients who were in better health over black ones who were sicker. Apple’s credit card is an example of AI prejudice because it gave women less credit than males did in similar situations. The credibility and reputation of the business could be damaged by AI bias if it leads to unfair and damaging outcomes. This is bad for business and will only serve to grow scepticism of AI’s usefulness. Ethical AI is needed to prevent such mistakes.
How can we define ethical AI, and why do we need it?
Ethical AI is described as AI that follows clearly articulated AI ethical norms concerning essential values, including individual privacy and safety, nondiscrimination, and fairness. The primary objective of ethical AI is to develop a just AI that respects human rights and does not put people in harm’s way. Because most machine learning algorithms rely on the historic data collected/generated by humans, it is inevitably tainted by human bias. Furthermore, most deep learning models are complex and unable to describe the decision-making process. In a similar vein, an open letter was submitted to the United Nations in regard to certain autonomous weapons meant to operate on the battlefield, which might harm human lives and, in some situations, be utilised by terrorists against innocent people. Ethical AI is crucial to prevent bias in machines and provide context for their actions. In addition to stopping the misuse of autonomous weapons, it protects users’ privacy by instituting safeguards for their data throughout its collection and storage phases.
Can you define the guidelines for Ethical AI?
In 2018, the UK’s House of Lords published a report on artificial intelligence (AI) that outlined five principles for ethical AI. These principles are as follows: 1) AI must be a force for good – and diversity; 2) Intelligibility and fairness; 3) Data protection; 4) Flourishing alongside AI; and 5) Confronting the power to destroy.
- AI must be a force for good – and diversity: AI applications should be developed in ways for the good and benefit of humanity. Additionally, this concept argues for the design and execution of AI applications by utilising a common ethical framework that defines the potential positive outcomes of AI technology.
- Intelligibility and fairness: A second guiding concept stresses the importance of AI functioning and developing within the bounds of human understandability and justice. Due to the many procedures and layers through which machine learning models have passed, their decision-making processes are opaque at best. This guiding concept introduces technical openness and transparency to help break down such obstacles.
- Data protection: It costs an average of $3.86 million per breach to replace the personal information of a single person whose data was lost, stolen, disclosed, or hacked. When basic human rights are violated in this way, people naturally become more sceptical about AI and its potential uses. This approach emphasises allowing the corporation fair access to a reasonable quantity of data while respecting individual privacy in order to prevent such a loss.
- Flourishing alongside AI: As the number of AI-based tools available to the public grows, so too should the expectation that all people have access to the education and opportunities necessary to flourish intellectually, emotionally, and economically. In addition, 73 million US jobs will be lost to AI automation by 2030. Thus, the government should invest in workforce training and employment areas that will be affected.
- Confronting the power to destroy: Dealing with destructive power: AI-based autonomous weapons, such as killer robots, could one day wipe out humanity. Researchers and developers of AI applications, therefore, need to think about how they could AI can be misused and where possible involve humans in the loop for crucial decisions.
What are some examples of contemporary ethical AI practises being used by different organisations?
Google Health is working on an advanced AI application for detecting breast cancer, and they want to make sure it works well for people of all races. A similar study, titled Transparency Tools for Fairness in AI, suggested a new instrument for policymakers to utilise when evaluating and rectifying unfairness and prejudice in AI systems (Luskin). AI Fairness 360, an open-source toolset developed by IBM, helps detect and correct bias in machine learning models at any stage of the AI development process. The Seclea platform has a feature that can help you find and fix bias and prejudice in your machine learning models. As an additional measure, Microsoft released Fair to Learn, an open-source toolkit for data scientists and developers to evaluate and enhance the fairness of their AI systems. Meanwhile, Google employed what-if visualisation tools as a useful tool to stop AI from making poor decisions based on the unfairness of the world as it is.
In the Future, AI Will Be Used in a Responsible Manner
By preventing unfair and biased conclusions, the ethical AI concept improves the credibility and performance of AI software. Furthermore, it is essential to describe the machine’s decision-making process in detail, as this facilitates the identification of errors and biases in the data. Big businesses’ collection and use of personal information should also be subject to government oversight and regulation. These AI-based measures will help people, businesses, and communities alike see the value of AI ethics and develop confidence in the technology. Therefore, a trustworthy AI would be one that welcomes all users, can be easily explained and makes ethical use of collected information.
Building Ethical Artificial Intelligence!
Organisations must adopt clear governance policy with mechanisms to enforce and monitor adherence to Ethical AI principles.
Seclea provides tools for your AI stakeholders (Data Scientists, Ethics Leads, Risk & Compliance Managers) to enforce, monitor and achieve compliance with the governance policies at every stage of the AI lifecycle, from AI development to deployment activities with real-time monitoring and reporting. We are here to help; email us at email@example.com or fill out the short form.