The Easy Ethics of AI – Empowering Positive Impact

What does AI mean, and what does ethics mean? How about when they’re placed together?

“The first rule of robotics: Do no harm.” – Dr Susan Calvin, I, Robot.

Artificial intelligence (AI) is a hot topic at the minute. And the powerful potential of this technology has naturally become a large part of mainstream discussions.

Yet AI’s growing impact comes with a mirrored growth in concerns about the ethical implications of this new technology.

This new, gargantuan technology.

With human-level intelligence.

that’s set to change the way we live.

Uh-huh. The impact could be (will be…already is…) huge! So we’ve got to prepare with care.

AI meets ethics

As with any new technology, we must always consider the surrounding moral and ethical implications. The intersection between AI and ethics thus aims to ensure that we develop and deploy AI responsibly. And that we distribute the benefits of this new technology across society fairly.

Why is AI Ethics important?

Well, AI will transform many aspects of society; from healthcare, retail and education, to transportation and entertainment.

But, if it isn’t developed and deployed correctly, it could produce an army of negative consequences. Bias, discrimination, infringement of human rights… All the nasties. And none of us wants any of that charging our way, do we?

That said, learning about AI ethics is essential to ensure we develop the tech in the right way. And knowing AI’s ethical implications can help mitigate the risks and maximise the benefits… For the greater good. Double win!

The bottom line? 

In line with UNESCO’s Recommendation on AI Ethics, the

• Respect, 
• Protection, and
• Promotion

of human rights, fundamental freedoms and human dignity are all unnegotiable requirements.  

So, how do we achieve this?

Key Principles of AI Ethics

Transparency

AI systems must be transparent and explainable. And their decision-making processes must be clear and understandable.

Explainable AI (XAI) algorithms provide visibility. That’s because they allow users to understand how the algorithm has been used to arrive at its decision.

Use Case Application

A fashion retailer using an AI-powered personal shopping assistant may use XAI algorithms to explain how their e-commerce site assistant makes clothing recommendations. This way, consumers can understand how their purchase history and browsing behaviour are analysed. As a result, they’ll feel a little less like they’re prime-time TV to ‘big brother‘ and be more trusting of the brand with which they’re shopping.

Read more: 6 Ways the Exarta Metaverse Will Revamp Retail.

Because that’s the goal, right? To solve that big bad pain point of easing customer worries to increase adoption of your services and products. 

Transparent AI-powered businesses build trust with their customers. They drive growth by being honest and by being clear. And by addressing concerns around data privacy.

AI will have potential customers running at you with open arms, like a toddler to its parent holding a big shiny lollipop. Your brand is the parent, and our delicious AI solutions are the sweetness on a stick. Robust in structure; deliciously enjoyable in experience.

Over time, transparency creates genuine, long-lasting brand-to-consumer relationships. And these always result in higher customer satisfaction. After all, the longer you lick a lollipop, the longer you savour the enjoyment, right?

Accountability

AI developers and distributors must take responsibility for any potential consequences of AI usage.

That’s why at EXARTA, we design AI systems through Zeniva that offer suitable chances for feedback and applicable explanations. All wrapped up in a juicy appeal to your customers, of course.

Moreover, the Zeniva AI Business Suite is subject to the right human direction and control by the businesses that install it.

Because while humans may opt to utilise AI systems for efficiency, it’s ultimately up to us to surrender control in certain situations. Although we can turn to AI systems for decision-making and action, we can’t totally relinquish our responsibility. We mean, it’s generally not recommended to entrust AI systems with life-and-death decisions.

Granted, EXARTA is the power behind the AI technology. The Web3 experts so you don’t have to be. But that doesn’t mean it’s all on us. You must maintain a goal of using AI only to benefit your organisation, customers and (if you’re feeling extra generous) society at large. Nothing more, nothing less. It’s that simple!

Safe Testing

Unwanted harms and vulnerabilities to attack must be avoided and addressed when implementing Zeniva.AI. The next step is prevention and elimination. This is to ensure human, environmental and ecosystem safety and security.

At EXARTA, we only develop and enable safe and secure AI practices to avoid unintended results from AI that could create risks or harm.  How? Through the development of sustainable, privacy-protective data access frameworks. We’re designing the Zeniva AI Business Suite under the best practices in AI safety research.

Fairness

The benefits of AI should be accessible to all. That’s why, at EXARTA, the protection and promotion of diversity and inclusiveness are ensured throughout our development and deployment of Zeniva.AI technologies.

For example, the use of AI algorithms and datasets has the potential to either mirror, amplify, or mitigate unfair biases.

And we acknowledge that identifying fair versus unfair biases can be complex. That these concepts can vary among different cultures and communities.

So, we strive to prevent any unjust consequences that may affect individuals. We focus on sensitive demographics related to human dignity, such as:

• race,
• ethnicity,
• gender,
• descent,
• age,
• sexual orientation,
• language,
• ability,
• national origin,
• ethnic origin,
• social origin,
• political or religious beliefs,
• and any other grounds.

Use Case Application

Companies can use AI for hiring and promotions.

Machine learning algorithms can analyse candidate resumes, cover letters, and job applications. They can also assess candidates’ skills, experience, and qualifications based on predefined criteria.

AI can also assist in matching current employees with internal job openings and recommending career development opportunities based on their skills and interests.

Read more: What is the Metaverse? | EXARTA Metaverse

All sounds positive. But if you decide to use AI for internal operations, you must take steps to guarantee fair, unbiased decision-making. Otherwise, what’s the point?

Here’s how:

• Regular auditing and evaluation. Conduct regular audits and assessments of your AI-powered recruitment and promotion systems to identify and mitigate potential biases. (With Zeniva’s AI-powered collation of data and analytics, this process is as easy as 123).

• Diverse training data. Ensure the training data used to develop AI algorithms is diverse and representative of the entire candidate pool. Focusing on including underrepresented groups will help reduce bias in the algorithm.

• Algorithmic transparency. Install explainable XAI algorithms that provide clarity into how the decisions are made. This can help identify and correct biases and increase your trust in the AI system.

• Human oversight. Incorporate human oversight in the decision-making process. For example, your recruitment managers can review the decisions made by AI algorithms and ensure that they are fair and unbiased.

• Fairness metrics. Use fairness metrics to test the fairness and accuracy of the AI system. This can help you identify any biases and provide insights into improving the system.

• Regular updates. This includes updating training data and algorithms to account for changes in the candidate pool and any new biases that may arise.

For instance, Zeniva’s multilingualism and cultural diversity sets it apart from competing models. (Not a plug, not a plug, not a plug). We just want to make your life as easy as possible, you know.

Privacy

Privacy must be respected, protected and promoted throughout the life cycle of AI systems. Thus, AI system data must be collected, used, shared, archived and deleted in ways consistent with international law. Data collection must also respect relevant national, regional and international legal frameworks.

At EXARTA, we incorporate strict privacy principles in developing and using Zeniva’s AI technologies.

Here are 5 means of how we make that happen:

1. We always allow for notice and consent,

2. We build architectures with privacy safeguards,

3. We provide appropriate transparency and control over the use of data,

4. Our technologies do not collect or use personal data without the explicit consent of individuals, and

5. When data is collected, we store it securely.

Use Case Application

Medical AI systems must keep sensitive patient records secure at all costs.

Read more: Gen-Z Marketing 101: Unlocking the Secrets to Reaching Young Shoppers.

Healthcare organisations seeking to use AI can assist high-level security in the following ways:

• Encryption. AI can use encryption techniques to secure sensitive patient data. This ensures that unauthorised personnel cannot access the data even if they manage to get hold of it.

• Adequate data protection frameworks and governance mechanisms should be established in a multi-stakeholder approach at the national or international level, protected by judicial systems, and ensured throughout the life cycle of AI systems.

• Authentication. AI can also use authentication techniques to restrict access to medical patient data. This means that only authorised personnel can access the data.

• Anonymisation. AI can help to anonymise patient data to prevent the data from linking back to individual patients. It removes identifying information such as names, addresses, and social security numbers.

• Access Control. AI can use access control techniques to restrict access to sensitive patient data based on a user’s role and level of authorisation. This means that only authorised personnel can access specific parts of the data.

• Regular Backups. AI can regularly back up patient data to ensure it is secure in case of a breach or data loss. Storing backups off-site can prevent data loss in unforeseen events (such as a fire).

• Monitoring and Alerting. AI can track access to patient data and alert administrators if there are any suspicious activities or breaches.

With AI, used appropriately, healthcare providers can provide better care and maintain patient trust by ensuring that patient data is secure.

Human rights

New technologies must provide new means to support, defend and exercise human rights rather than violate them.

AI should thus be developed and utilised in a way that respects fundamental ethical values.

That’s why at EXARTA, we will not develop the following:

• AI technologies that cause harm or pose a significant risk of harm (except where the benefits outweigh the risks and appropriate safety measures are in place);

• AI technologies that gather or use information for surveillance;

• AI technologies whose purpose violates widely accepted principles of international law and human rights.

AI systems should not cause harm or subjugation to any individual or community, be it physically, economically, socially, politically, culturally, or mentally, at any stage of their life cycle. 

Instead, AI should improve the quality of human life.

Read more: AI Marketing Isn’t Replacing Human Marketers, It’s Helping Us Do a Better Job.

Wrapping up AI & ethics

By promoting transparency, accountability, fairness, privacy, and respect for human rights, we can create a more just and equitable future for all.

A final word from Exarta.

While this is how we approach AI, we understand there is room for many voices in this discussion. As Exarta grows and as our AI technologies progress, we, with open arms, welcome investors, partners, and stakeholders to promote thoughtful leadership in our continuous work in this area, drawing on scientifically rigorous and multidisciplinary approaches.

And in honour of being transparent, we’ll continue to share what we learn, as we learn, to improve how we develop our AI business technologies and how our customers implement them into their own strategies.

The road to the Metaverse isn’t always clear-cut. But our plan for Zeniva is long-term. So, while our approach will remain consistent with our values, we’re willing to be flexible as the world around us changes.

And we welcome you to join us on our journey.