Why developing an AI Code of Ethics may be the key to unlocking even more growth
The Artificial Intelligence (AI) race is well underway. Companies are spending to compete for shares of an uncapped marketplace. Results are being had at record pace. New products, developments and mind-blowing solutions are being rolled out across AI newsletters, forums, social platforms, blogs and even (or especially?) during the Super Bowl.
Albert Einstein had a point when saying, “We cannot solve our problems with the same thinking we used when we created them.” Boy was he right.
Industries are booming. It was recently reported that the automotive AI market alone will grow from just over $3 billion to nearly $36 billion in the next 10 years. Factors such as R&D and autonomous features and vehicles are key movers in this space.
But amid the explosion of use of AI, how we use AI is growing in importance as well. The imperative for ethical AI in business is highlighted by instances where its misuse has led to significant ethical dilemmas and outcomes.
Look no further than all the way back to February 2024 as an example of where a lack of standards and ethics can be seen in demonstrating the potential pitfalls of AI at the highest levels of government and politics. The result was an AI-generated ‘victory speech’ from a candidate jailed behind bars touting his political party’s electoral gains in perhaps the least credible election of its kind, according to The New York Times.
As AI technology becomes increasingly integral to business operations, embedding ethical considerations into digital transformation strategies becomes not just a moral imperative but a business necessity.
Nothing New: Precedent of Ethics Codes in Numerous Industries
Before delving into the ethics of AI, it's important to recognize that codes of ethics have long been a cornerstone in various professional fields:
Journalism
Ethics in journalism emphasize principles like truthfulness, accuracy, objectivity, impartiality, fairness, and public accountability.
The Society of Professional Journalists (SPJ) Code of Ethics advises journalists to seek truth and report it, minimize harm, act independently, and be accountable and transparent.
Legal Industry
In the legal field, ethics codes focus on responsibilities like client confidentiality, avoiding conflicts of interest, and maintaining professional integrity.
The American Bar Association's Model Rules of Professional Conduct provide a framework for ethical legal practice, including duties to clients, the legal system, and the public interest.
Medical and Healthcare Industry
Medical ethics are guided by principles such as patient autonomy, beneficence, non-maleficence, and justice.
The Hippocratic Oath, one of the oldest binding documents in history, is an oath of ethics historically taken by physicians. It emphasizes the ethical practice of medicine, including confidentiality and the principle of "do no harm."
These established ethical codes in journalism, law, and medicine demonstrate the significance and impact of ethical guidelines in professional practices. They serve as a precedent for the emerging field of AI ethics and as a common – and best – practice for a nascent industry.
What are the 5 Ethics in Artificial Intelligence?
AI ethics revolves around five fundamental principles:
Transparency: AI systems must operate transparently, with clear explanations of their decision-making processes.
Impartiality: AI should be unbiased, ensuring fairness in decision-making.
Reliability: AI should not cause harm to users or society.
Accountability: There should be accountability for AI decisions and actions. Prevention is as important as any cure for anything that goes wrong, meaning that constant supervision of the system is critical.
Security & Privacy: AI must respect and protect user data privacy.
Here’s an excellent summary of these principles from Coursera AI Ethics.
If you’re a fan of John Oliver, you might know that the HBO host offered a solid take on AI almost a year ago. One of the significant callouts was that of bias within the data set. When prompted to name top performers in various industries, the AI results almost always provided lists of men. That’s a function of the data within the model. (What’s a model? Here’s a not-overly-complicated summary on the distinctions between AI, Machine Learning (ML) and Deep Learning (DL), along with models for each.)
Bottom line: There’s a gap between data and outcomes. Which leads to some ethical concerns.
Ethical Concerns of AI
Three major concerns in AI ethics are:
Bias and Discrimination: AI can perpetuate biases from training data, leading to discriminatory outcomes.
Loss of Privacy: AI's data analysis capabilities risk eroding privacy if not managed correctly.
Autonomy and Job Displacement: There's fear of AI automating jobs, leading to job displacement.
Insights into addressing these concerns in real-world scenarios are explored in this post-Davos VentureBeat article from Gary Grossman, Edelman’s EVP of technology and its global lead of the Edelman AI Center of Excellence.
TLDR: Remember the phrase “prudent stewardship.” Prudent stewardship of AI by humans involves not only the responsible management and use of Artificial Intelligence technology but also a commitment to its ethical application.
As the integration of technology in business becomes a necessity amid the digital transformation era, so too is the integration of AI within business segments. But as we balance the changing nature of our professional world thanks to the solutions provided by AI, perhaps there’s one more vision from Einstein to consider.
Ethics are an exclusively human concern.
Comments