Ethical Frameworks Will Guide Emerging Technologies
May 27, 2021 / Peter Altabef
May marks the beginning of graduation season in many parts of the world, with the distribution of diplomas to students at universities. It also initiates a new chapter as graduates full of talent and curiosity prepare to enter the workforce. Yet, we should ask this question: Have their universities taught these eager graduates and future leaders to examine the ethical implications of emerging technologies that are already important and will become more so in the years and decades ahead?
The increasing scale and demand of artificial intelligence (AI) is reinforcing the need for companies to develop and leverage machine learning (ML) and AI responsibly, transparently and ethically.
Just as we and our peers are the decision makers of today, these graduates are our decision makers of tomorrow. It is critical, then, that we engage with them and ask questions about how they expect these technologies will impact the way they frame the world.
The need for AI ethics
Because automation enables us to analyze and decipher data at an accelerated rate, there is a heightened focus throughout the IT industry on using it to generate data-driven decisions. AI makes those decisions in part by attempting to mimic human thinking to solve problems. However, as humans we come with inherent biases and form decisions based on our personal experiences. Those experiences shape our behaviors and our data, the foundational elements of machine learning. Without understanding those biases and accounting for them, AI has the potential to bury them inside algorithms that few have access to or understand and amplify biased datasets at massive scale.
A one-dimensional application of AI can produce flawed outputs and unforeseen and unintended consequences. To be truly effective in driving positive outcomes for businesses, governments and communities, AI solutions must have an ethical dimension, following principled design guidelines that actually do distinguish between good and bad outcomes.
In the interest of rapidly delivering successful outcomes to clients, companies shouldn’t compromise their integrity. By ethically leveraging emerging technologies such as AI and ML, companies will drive innovation and expand outcomes for existing clients while also attracting new ones.
It is our responsibility to be transparent about the decisions we make around AI and ML and the technology we implement. Transparency reinforces trust as the foundation for relationships with clients. Our clients expect us to help them transform their capabilities, so it is up to us to hold our services and solutions to the highest standard.
Educating the future workforce
Ethics in the application of advanced technology is important not only to the future of our business, but also for the next generation of workers. I am giving a presentation this fall at a university on the importance of crafting ethical frameworks for AI and biometrics. My presentation will emphasize how ethical frameworks can help individuals shape their own evaluation. The four questions below will frame the presentation:
- Is the system fair?
- Does the system affect us beyond what it is intended to do – is it limited or too open to unintended consequences?
- Will the information it collects be safeguarded and not, for example, sold to others without permission?
- Can one learn enough about this system, even if not technologically-oriented, to make a reasoned decision?
These questions are important but not simple. For example, defining “fairness” is fraught with complexity. There is hard work to be done.
The best, most rewarding and most productive decisions are ethical ones.