AI Ethics: How to Innovate the Safe and Responsible Way

Every day, you interact with AI. It suggests your videos, powers your smart home, and even screens your job applications.

But what happens when these unseen algorithms make a mistake?

As artificial intelligence becomes ingrained into every aspect of our lives, we need it guided by transparency, fairness, and accountability. For now, only 52% of companies practice some level of responsible AI, and 79% say implementations are limited in scale and scope. 

Meanwhile, 35% of global consumers trust how organizations are implementing AI. We’re taking steps toward making AI ethics the norm. And by reading these lines, even you are becoming a part of the solution since awareness and engagement are key.

So, let’s explore how we can contribute to a more ethical and transparent AI world, what ethical challenges to expect, and how to overcome them.

What are AI ethics?

AI ethics is the study and application of moral principles in artificial intelligence. It's not just one field but a vibrant, multidisciplinary area that combines insights from philosophy, law, data science, sociology, and more.

Because artificial intelligence impacts every facet of our lives, we want it to work for the good of all, minimizing potential harm. But it can’t do that without fairness, transparency, and accountability.

Let’s take a look at these essential AI ethics attributes.

1. Fairness

Any AI system should make fair decisions that don’t discriminate against race, gender, socioeconomic status, location, etc. AI systems are used on such a large scale internationally that bias can affect many people’s lives. AI ethics help set clear rules and steps for how we feed the machine-learning models and train their creators.

2. Transparency

Transparency is about making how AI processes decisions clear and understandable to users and stakeholders. Transparent AI code increases consumer trust (which is great for business) and empowers human judgment about using AI systems. It reduces overall ethical concerns.

3. Accountability

We all enjoy celebrating when artificial intelligence does something amazing. Yet, we must also own up and take responsibility when things don't go as planned. Accountability ensures that AI system designers, developers, and deployers take responsibility for their AI code and work to resolve errors.

Why are AI ethics important?

AI ethics lead to public trust in technology, legal and financial stability for companies, and a harmonious and prosperous society. 

In contrast, unethical artificial intelligence leads to:

• Bias and discrimination: AI technologies reflect the data they're fed. When your data is biased, your AI's decisions will be biased — causing discrimination, unfair treatment, and an overall negative societal impact. A notorious example of biased AI came from Amazon's hiring algorithms. Their AI code favored male candidates over female ones because training data reflected a historical, biased hiring pattern.
• Loss of privacy: AI's ability to analyze vast amounts of data makes it a powerful tool for insights and innovation. Conversely, it can lead to significant privacy invasions and data breaches. For example, in 2023, Samsung suffered when developers unintentionally exposed sensitive data while integrating their code into ChatGPT.
• Misuse and abuse: AI tools can also be used for wrong purposes, like creating deepfakes, enabling intrusive surveillance, and developing autonomous weapons. Governments and organizations are increasingly wary of it. In response, James Cleverly, the Foreign Secretary of the United Kingdom, recently embarked on a unique collaboration with the AI video generator Synthesia to advocate for the safe and responsible use of AI technologies.

The impact of AI ethics across sectors

To ensure artificial intelligence does as much good and as little harm as possible, we need a solid mix of innovation, regulation, and ethical foresight across all business sectors. Below, we look at how AI is being used in various fields.

Healthcare

Human life, in general, and healthcare, in particular, benefit immensely from AI. Machine learning models can predict disease onset, chatbots facilitate appointment scheduling and patient communication, and AI-driven robots assist in surgeries.

However, minimizing AI risks in health care is challenging. Such powerful software must be monitored to avoid biases in diagnosis and ensure patient data privacy. There’s a critical need to maintain patient autonomy so everyone gets equitable treatment.

Finance

In finance, AI tools automate plenty of routine tasks. Investors can receive personalized financial advice, portfolio optimization tips, and access to algorithm trading, whereas law enforcers can use AI programs to detect fraud and enhance risk assessments.

The big question data scientists and AI developers pose here is, “How do we maintain trust and ensure fairness in algorithms?” We all want to avoid unethical outcomes and AI code making bad financial decisions or causing legal issues.

Criminal justice

From legal document analysis to automating judiciary processes, artificial intelligence is helpful in any justice department. Now, AI research can even assist in predictive policing and crime analysis. Yet, any responsible AI system needs to go to extreme lengths to ensure accuracy, respect civil liberties, and reduce legal risks.

Education

Artificial intelligence helps foster human intelligence with applications in education, learning, and development. The use of AI technology personalizes learning, provides insights into student performance, and automates grading. Plus, virtual learning environments broaden access to education.

However, using AI code for educational purposes must carefully trade the data privacy line. Moreover, we need equitable access to resources and to remove human biases from content development and assessments.

Agriculture

A world where we use AI models to analyze soil health, optimize crop yield predictions and pest control, and automate harvesting isn’t just a dream. We’re already living in it. AI does all this, improving the efficiency of production and supply chains.

One of this sector's main AI ethics challenges is ensuring sustainable practices. Since agriculture is critical in rural areas, we want to consider AI’s impact on employment and see how we can make technical solutions accessible for small-scale farmers.

Retail

AI, machine learning, and natural language processing work wonders in retail by powering dynamic recommendation engines and intelligent customer service chatbots. It delves deep into predictive analytics to understand consumer behaviors and personalize shopping journeys. It's a powerful tool in logistics as it's capable of streamlining inventory management optimizing the entire procurement workflow.

Deploying trustworthy AI in retail, however, comes with ethical strings attached: the potential impact of AI on job availability and the critical need for transparent use of consumer data.

Transportation

You're probably thinking of self-driving cars, but AI can contribute to any type of transport vehicle operation. Think about route optimization, predictive maintenance, and autonomous vehicles. It just makes transport more efficient while also aiming to make it safer.

Faulty AI algorithms could cause accidents in anything self-driven or AI–routed — cars, trains, airplanes — which is why reliability is critical. But next to safety, ethical concerns related to moral decision-making in crises, accountability, and liability also arise here.

The 4 principles of AI ethics 

Principles give developers and businesses a moral compass to guide their AI development decisions. 

There are some tough choices to make, like balancing safety with surveillance or crime hotspot predictions with racial discrimination. Principles exist to help developers know how to strike a balance.

1. Beneficence: The term comes from Latin and is often used in medical and healthcare ethics, with the sense of “doing good,” promoting well-being, and preventing harm. As a principle, it emphasizes the creation of technologies that positively impact society, such as improving healthcare diagnostics or enhancing educational resources.
2. Non-maleficence: Closely related to beneficence, non-maleficence is about commitment to avoid harm. It involves careful testing and thinking about right and wrong at every step of making and using AI.
3. Autonomy: Such systems that support and enhance human decisions ensure that individuals remain in control of how AI models impact their lives. Autonomy includes human participation with consent over data use and the possibility to opt out or modify interactions with AI systems.
4. Justice: This principle ensures that the benefits and burdens coming from the use of AI are distributed fairly across society, all demographics are represented in datasets, and the technology does not discriminate against any group. This principle is about ensuring AI regulations and minimizing legal issues.

Organizations that promote AI ethics

Several organizations provide guidance, support, and insights on how to align AI development with ethical principles. Let's take a closer look at some of these key players, from both the public and the private sector, that help us stay accountable for the principles of AI ethics.

AlgorithmWatch is a non-profit human rights organization. They monitor algorithmic decision-making processes, focusing on their impact on society and human behavior. Their goal is to hold companies accountable for the ethical implications of their algorithms, ensuring transparency, fairness, and a more trustworthy AI.

AI Now Institute is an AI research center dedicated to understanding the social implications of artificial intelligence. They explore how AI models impact fields like labor, healthcare, and criminal justice and advocate for AI's responsible and ethical use.

DARPA is primarily known for its role in developing emerging technologies for the U.S. military, but it also plays a significant part in AI ethics. Their initiatives often include ethical considerations and safe AI practices, focusing on advancing AI technology to align with ethical standards and promote responsible innovation.

CHAI, the Center for Human-Compatible Artificial Intelligence, focuses on designing AI systems that operate according to human principles and values. They research many different areas, advocating for AI that makes our lives easier but also safer.

NASCAI is a collaborative effort that brings experts from various sectors together to promote AI safety and ethics. They work on creating guidelines and frameworks that help in the responsible creation and deployment of AI technologies.

Challenges of AI ethics in practice

AI technology is constantly changing, new layers of difficulty arise, and bringing AI ethics into the real world can hit many speed bumps.

For instance, autonomous systems designed and trained on data sets that may contain biases can perpetuate or even amplify those biases. So, we need to develop fair, unbiased algorithms, even though people worldwide have diverse, sometimes conflicting definitions of fairness.

Then, as AI systems process vast amounts of data sets, user privacy, and responsible data management are a must. But ongoing challenges prevail…

• How can data scientists get useful insights from all that data while respecting individual privacy and human dignity rights and preventing breaches?
• How do we ensure the data sets we train AI systems with are relevant, unbiased, and representative?

The goal isn’t to inhibit innovation but to shape it to promote human well-being and respect fundamental human rights under regulatory, ethical frameworks. Too little regulation of intelligent systems can lead to ethical lapses and harm, while too much can stifle innovation.

Sal Khan, the founder of the Khan Academy, has some pretty powerful thoughts on the topic of artificial VS human intelligence that he shared in a TED talk on “How AI Could Save (Not Destroy) Education”:

AI ethics must address concerns and include voices from different demographics, disciplines, and cultural backgrounds in the development and governance of AI systems. This means global collaboration is a must. A mix of perspectives helps spot and fix ethical issues that might be missed otherwise.

7 Tips on how to establish and promote AI ethics

Making ethics a core part of an organization that develops or employs AI systems is a process. It takes collaboration, continuous learning, and adaptation. Here are some key steps to effectively embed AI ethics into your organization's fabric:

Tip 1: Develop ethical principles

Start by defining your core values and tailor them to fit your industry, geographical context, and application of AI. Whether you choose transparency, fairness, non-discrimination, accountability, etc., these principles should guide all your AI-related activities and decisions.

Tip 2: Create ethical guidelines and standards

Develop actionable guidelines that incorporate industry standards and best practices for ethical AI. These guidelines should provide clear directions on implementing ethical principles in your everyday AI operations and decision-making.

Tip 3: Implement governance structures

Set up an ethics board to oversee and enforce ethical practices. This structure will help maintain ethical standards and address ethical dilemmas or breaches.

Tip 4: Foster a culture of ethical awareness

Cultivate an organizational culture that emphasizes ethical awareness. Regularly train and educate your employees so that everyone understands the importance of ethical AI. And always encourage open dialogue on moral principles or ethical issues.

Tip 5: Engage in multi-stakeholder collaboration

Partner with experts in the field and develop industry and academic partnerships. Collaboration with diverse stakeholders gives you broader insights and helps shape well-rounded ethical practices.

Tip 6: Adopt a continuous improvement approach

AI and its ethical implications are constantly evolving. Adopt a continuous improvement mindset, and regularly monitor and adapt your AI ethics framework to keep pace with tech advancements and societal shifts.

Tip 7: Promote transparency and accountability

Use transparent and understandable AI systems. Explain how these systems work and set up mechanisms to hold your organization accountable for the AI's outcomes. Plan for regular ethical audits, gather stakeholder feedback and set performance metrics for fairness, accuracy, privacy preservation, and other ethical aspects.

Synthesia’s stance on AI ethics

As a leading AI video creation platform, we aim to transform how videos are produced and make text-to-video accessible to companies and organizations worldwide.

But while we revolutionize the video creation landscape, we want to set the bar high for ethical generative AI.

After all, our users generate videos from plain text, using lifelike AI avatars that can narrate almost anything in 130+ languages. The potential for misuse cannot be ignored, and reinforcing ethical standards and responsible moderation is critical.

Our CEO, Victor Riparbelli, has been vocal about these challenges, emphasizing the need for ethical AI in various keynotes and TV appearances, including his 2023 SaaStock keynote.

Our approach to AI ethics is comprehensive and forward-thinking. As the world of artificial intelligence media advances, we lead by example, relying on the following pillars of ethical AI:

Consent and Control

Central to Synthesia’s ethical framework is consent. We advocate for creating AI avatars only with explicit human consent, steering clear of impersonations. Our generative AI platform is designed to ensure a secure environment, with rigorous content moderation and a dedicated Trust and Safety Team that safeguards responsible use and data security.

Transparency and Disclosure

Synthesia champions transparency across all creation tools and distribution processes. We believe in public education and industry-wide collaboration as key factors in ensuring platform safety and combating the potential risks associated with synthetic media.

Collaboration for a better future 

Recognizing the challenges of AI ethics, we actively collaborate with regulatory bodies, media organizations, and academic institutions. We are a launch partner to the Partnership on AI (PAI) on Responsible Practices for Synthetic Media and an active member of the Content Authenticity Initiative, reflecting our commitment to shaping a responsible AI future.

Continuous evolution and adaptation

The AI landscape is dynamic, with evolving guidelines and regulations. Synthesia navigates ethical challenges and stays ahead by continuously refining practices. We verify credentials for news content creation and collaborate with experts in curbing abusive content. This commitment to evolution and adaptation ensures we remain at the forefront of ethical AI governance.

Embrace ethical AI along with Synthesia

The best way to contribute to an ethical AI-powered world is to partner with those who support ethics and put people before anything else.

Learn more about Synthesia’s commitment to AI ethics and safety. Discover how to create AI videos in a structured, regulated, and safe environment.