Artificial Intelligence (AI) is the digital technology that has greatly influenced human development. Every tech giant is doing its best to develop an advancement in AI technology. It implies that Ethical problems must be explained, the risks associated with the development of Artificial intelligence. So many basic questions like what’s the use of the systems, risks, dangers involved, functions of the systems, and how to control it.
Artificial stupidity: How can we guard against mistakes?
Practical learning births intelligence both in machines and humans. Systems do have a training period to learn how to discover accurate patterns and act based on their input. After completing the training, then it undergoes a test phase to be sure of its performance.
During the training period, the system can’t deal with all the possible examples that the world. Systems can be fooled by humans. For instance, random dot patterns can cause machines to perceive absent things. If we depend on AI to lead us to a new era of labor, efficiency, and security, we must ensure that the machine performs as expected and can’t be subdued by anyone.
Inequality: How can we share the wealth developed by machines?
Most companies are still relying on hourly work as regards products and services. However, with AI, a company can extremely reduce its dependence on the human workforce, which implies that the revenue would go to few staff. Those who have ownership in AI-driven companies will earn more money.
People are already experiencing a large wealth gap, where start-ups get the largest share of the economic surplus they develop. In 2014, the three most prominent companies in Detroit and the three most significant companies in Silicon Valley had similar revenues. But Silicon Valley has ten times fewer employees. If we’re pondering on a post-work society, how can we structure an equitable post-labor economy?
Security: Keeping AI safe from evil ones?
Powerful and efficient technology can also be used for both good and sinister reasons. This isn’t only applicable to robots produced to substitute autonomous weapons and human soldiers, but to AI systems which can cause significant damage when used evilly. And this makes Cybersecurity very significant and essential since we’re working with a system that has more capabilities and is faster than us on a larger scale.
Employment: Will AI replace the human workforce?
Most people are concerned about how AI-enabled systems will replace workers in several sectors. When AI is being referenced in the context of jobs, it brings mixed opinions and emotions. AI is known to be a job category killer. Jobs move from a place to another and also create new categories of jobs. So AI doesn’t destroy jobs. Research and experience revealed that it’s impossible that AI will replace all categories of work, particularly in customer service, government, professional services employment, transportation, and retail.
Transparency: Can we create transparency in AI decision-making?
Lots of approaches are used in machine learning. But, no machine learning has revitalized the AI market like deep learning. Deep learning is also known as the “black box.” We aren’t sure about deep learning functions, and it can cause a severe issue if we depend entirely on this technology to make vital decisions like who gets hired or loans application. AI systems that can’t be adequately explained must not be accepted, particularly in high-risk conditions. Explainable AI must be part of the formula if we want to get trustworthy and reliable AI systems.
Scope of resolving the ethical issues of AI
Ethical AI Framework
An incredible way of reducing ethical problems is by creating data, AI, and an ethical risk framework. The governance structure must be maintained. It reveals the ethical standards that must be followed. The framework will suggest how systems express and combine ethical principles. Also, it’s a quality assurance program used in measuring its efficiency in creating and designing ethical AI systems.
A committee like a governance board must be set up to monitor privacy, fairness, and other data-related risks and problems. It must be with ethics close to privacy, cyber, analytics, risk, and compliance. Professionals in subject matter and ethicists must be a part of the committee.
The committee will:
- To align AI ethics strategy to systems.
- Monitor legal and regulatory risks.
- Handle employees’ tasks and how they take care of these problems.
Optimize guidance and tools
The Ethical AI framework offers high-level guidance. Some AI systems need an explanation on it arrives at a final decision, particularly when the AI system’s decision has a strong tendency to transform life. However, the transparency of the model reduces as the accuracy of the prediction increases. In this situation, Product managers must know how to compromise.
Customized tools must be created to assist product managers in making decisions. Tools can examine the significance of explainability or accuracy for a specific system and give the product manager concrete suggestions on what to implement in that specific system.
Our world is divided into several respects, like history, politics, ethnicity, language, values, etc. This makes it challenging to describe legal and ethical issues. AI was designed by humans, which implies that it will be vulnerable. The vulnerabilities will have enormous implications if we have total reliance and dependence on computers. AI can identify something that isn’t working for humans and create its reasoning (moral and ethical) based on its knowledge and experiences. AI will concentrate on the rules that the machine follows or has already been programmed with.