AI & Ethics in the Media Industry
With the widespread adoption of AI technology, a multitude of ethical concerns are emerging. These range from biased algorithms to a lack of privacy to the replacement of human workers. From this, we see that the adverse impacts of AI extend beyond individual harm and actually encompass broader societal repercussions.
In our whitepaper on AI in the media industry, we explore the ethical considerations that must drive AI innovation and adoption. We discuss the current regulatory framework and policies for artificial intelligence, and look at how publishers can foster responsible AI use through industry collaborations and self-regulation.
Continue reading for an overview of what we tackle in the whitepaper, or download the full whitepaper here.
1. Potential biases in AI algorithms
AI algorithms have the potential to adopt biases present in their training data. This data often mirrors human thought processes as well as existing societal disparities. This can also be caused by skewed data samples and a lack of contextual understanding in AI.
We delve into several studies in the whitepaper that reveal the real-world impact of biased algorithms. In one conducted by the USC Information Sciences Institute, it was found that 38.6% of “facts” used by AI were biased.
We also look at how researchers are attempting to enforce fairness constraints on AI models through various methods, one being a socio-technical approach.
2. Privacy and security concerns
Many consumers are concerned about the safety of their information in AI-powered platforms. For media businesses, it is crucially important to enact robust data security and give consumers peace of mind that their information is safe.
In our AI whitepaper, we look at all the ways publishers can do this, including:
- Giving users the ability to consent to their data being collected
- Robust security measures like encryption and secure data storage
- Transparency around third party data sharing and how user data is being used
- Gaining consent for biometric data and facial recognition systems
- Clear policies on data retention and deletion to ensure user data is not stored forever
3. Transparency and accountability
When AI algorithms are difficult to understand, it heightens public fear, slows industry adoption and contributes to the ongoing distrust of AI systems.
Technical explainability, transparency around decision-making, and regular third party audits are all things we examine in the whitepaper that will be essential to removing the mystery around AI technology and encouraging its widespread acceptance.
One interesting statistic from the whitepaper highlights how responsible AI use is not only good for people, but good for business.
According to McKinsey, organizations that establish digital trust through ethical AI practices can expect at least 10% higher annual revenue and EBIT growth rates.
4. Human-AI collaboration
One of the biggest criticisms of AI technology is its potential to replace the human workforce and put people out of work. In the whitepaper, we address this concern, highlighting the importance of a synergistic human-AI collaboration.
By augmenting human capabilities with the advanced power of AI, many opportunities arise. Individuals will have the chance to upskill and pursue higher value roles, and media professionals will have the time and the resources to focus on creativity and community building.
According to one statistic we share in the whitepaper, 97 million new roles will emerge in response to the division of labor between humans and AI.
Through job augmentation and stirring a demand for new roles, we discuss how AI will never replace humans altogether, but work with them to achieve new heights of success.
Regulatory landscape of AI technology
Later in the whitepaper, we examine the existing regulations and policies surrounding the use of AI technology. We look at:
- The different approaches from different countries
- The importance of establishing adaptable regulatory frameworks
- How organizations can demonstrate responsible AI use in lieu of legislation by developing self-regulatory frameworks
Self-regulation emerges as the key thing publishers should do to dispel consumer concerns.
A massive 78% of Americans are concerned about the intent behind artificial intelligence. With an absence of legislation, voluntarily disclosing information and implementing a self-regulatory framework builds public trust and establishes you as a trustworthy company.
7 ways to promote ethical AI practices
Our whitepaper goes on to explore how ethical AI practices can be upheld through education and awareness. Here are the seven ways this can be done:
- Providing regular training for employees
- Establishing guidelines and policies
- Participating in industry dialogues focused on AI ethics
- Partnering with research organizations and AI ethics experts
- Creating educational content for consumers that explain AI concepts
- Promoting diversity and inclusion in AI teams to mitigate biases
- Regularly monitoring AI systems to address any unintended consequences
Download Lineup's whitepaper on AI in the media industry
To read about everything we’ve talked about in more detail, download our whitepaper. When you have a solid understanding of the ethical issues surrounding AI use, and what you can do to address them, it drives greater success in your AI endeavors and ensures you’re contributing to the wellbeing of society.