AI has swept the world. The rate at which various intelligent technologies are being adopted and implemented across different industries has been nothing short of magnificent. Despite the extensive list of positive implementations of AI, there is a darker side, as well. And, previously unforeseen situations are occurring, such as problematic issues with facial recognition and the development of bias in AI algorithms. This is why it is critical to building AI transparency into solutions.

While building any AI-based product or system in a short period and on a large scale, it must pass through an objective analysis. Organizations must evaluate both the positive and negative effects on customers, businesses, products, and services—and overall society. Besides, when exploited by the wrong people, AI can be a tool capable of inflicting dire consequences.

For example, COMPAS is an AI-based software tool used by several large US court systems to help determine sentences for offenders based on the likelihood of a criminal reoffending. A few years back, it was revealed that it was marginalizing subjects based on race—consistently (and falsely) predicting that black criminals are more likely to engage in recidivism than white criminals.

Other than being a global and cultural concern, AI is also a business concern. According to a recent Salesforce survey, 88% of consumers expect organizations to make positive contributions to society. Simply put, businesses must wield the might of AI with a careful, thoughtful approach. 

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What Does AI Transparency Bring to the Table?

The whole point of implementing AI is to empower people to make more rational and sensible decisions. But, the onus is on the human to decide whether AI is fulfilling their needs or if they should seek human help. For example, consider the AI-powered phone assistant: Google Duplex. The technology helps users perform routine tasks, such as booking a restaurant reservation for them. Yet, many people are still wary of leveraging it.

Since many people are hesitant to interact with AI, making it transparent will help. Transparency can help:

  • Reduce instances of fraud within the political landscape. We all know about political bots online. 
  • Boost the decision-making capabilities of individuals. If an AI system is transparent and consistently gives users valuable results, they will adopt it
  • Train and educate people. Although people may struggle using AI to achieve their goals at first, repeated exposure and positive experiences will likely make them continue using it 
  • Prioritize sincerity towards humans over pure transactionality. For example, and going back to the restaurant example, if the restaurant owner receives the same question from an actual human customer and an AI assistant, train it to notify the owner to respond to the customer personally. Robots aren’t concerned with a quick response or receiving that “human touch”— people are

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Monitor Ethics in AI

AI algorithms do generate biased outcomes; that’s a fact. This typically occurs because of low-quality data and poorly-designed algorithms. At times, flawed results make it appear as if the AI system is actively marginalizing a community, or not representing real-world populations. 

The existing use of AI applications in industries like financial services, medical diagnostics, and employment screening prove that a tiny irregularity can turn out to be quite costly and damaging to a company’s reputation. If data inputs are poor, the authenticity of AI-generated decisions is compromised because previous observations drive the results. Based on the use case, AI-powered outcomes can end up being unethical, illegal, and even myopic. 

To enforce an ethical use of AI, follow these steps:

Hire an Officer

Hire a Chief AI Ethics Officer. He or she can oversee the use of AI and ensure that you don’t cross any ethical boundaries, like generating gender bias or compromising the personal data of a customer or employee.

Educate Leaders

Your board of directors and CXOs must understand how AI impacts the organization. Show them what value it adds to the company, and what challenges may limit your efforts. You can also consider forming an ethics advisory board to oversee your AI initiative.

Keep an Eye on Government Regulations

The impact of government regulations has a direct influence on how organizations sell or apply AI. Businesses need to have a firm understanding of compliance mandates to prioritize the R&D budget more effectively.  Compliance mandates and regulations must drive the ethical design for AI before implementation. 

Pinpoint Risks

Organizations should know which areas are particularly prone to AI-related risks. When used by an HR department, for example, for candidate screening and other hiring processes, organizations need to ensure there is no bias. 

Plan Ahead

Organizations need to work proactively on how they plan to retain and train their employees for ethical AI initiatives.

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Assessing Data Privacy and Security from the Right Perspective

Security is a serious challenge for companies that implement AI, which is based on voluminous amounts of data. A considerable chunk of this data is highly sensitive—vulnerable to breaches and identity theft. To combat this, in 2018, the EU put the GDPR (General Data Protection Regulation) into effect. Any company doing business in the region must follow a strict set of regulations when storing, processing, and selling any data related to any EU citizens. 

In recent years, data science and machine learning community have established that more data is better.  However, as you manage risks across different segments, you might make a surprising discovery regarding your security—data is a massive liability. Because vast amounts of data are difficult to store, compute, and access securely, it is inherently at risk.  

Security researchers have agreed on a common conclusion when it comes to AI—if the creator of a model unintentionally unveils information about the inner-workings of an AI algorithm, it will introduce serious security risks. Hands down, organizations must recognize the fact that data security and privacy are critical matters in today’s world. As AI is more widely embraced, hackers will find bugs and loopholes to exploit. Organizations need to stay one step ahead.

Final Thoughts

Companies and governments need to ensure that data security, privacy, and transparency are at the core of their AI development programs. Governments are already doing this by introducing compliance regulations such as GDPR and the California Consumer Privacy Act (CCPA). All businesses must also provide more transparency into how their AI systems are securely handling personal data. Identifying and eliminating bias from AI algorithms is critical. They also need to recognize that they are accountable for any negative consequences that occur as a result of their respective AI implementations. 

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What Can Organizations Do? 

These concerns call for qualified, educated professionals who can help organizations and government entities approach AI with strong ethical and moral guidelines, and build proper processes to manage the implications and security risks. Simplilearn is a top educational resource for those seeking knowledge and certification in AI-related tools and career paths. Check out the AI courses to boost your career, or to upskill your existing employees in this rapidly growing field.

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