By Prangya Pandab - December 16, 2022 4 Mins Read
While the issue of how to use AI ethically has been widely discussed for some time, little has been done to put guidelines or ethical standards into place. Businesses need to stop just discussing the risks of unchecked AI and start putting practical strategies and tools in place if they want to start seeing actual changes in the industry.
Artificial Intelligence (AI) already has a significant impact on the daily lives of individuals in ways that, even only a few years ago, one could never have predicted. AI has permeated every aspect of everyday culture, including the workplace, from self-driving cars to voice-activated devices to predictive text messaging.
Although there is no denying the impact of Artificial Intelligence, consumers continue to have questions about the security and ethics of the technology. Because of this, businesses must attempt to ease these concerns by protecting customer data at all times when using AI-enabled technologies.
Also Read:The New Metrics for Managing Unstructured Data
Any company that interacts with consumers and uses Artificial Intelligence technology must exercise caution, especially when dealing with customer data.
When deploying AI, IT leaders must prioritize two tasks equally at all times: minimizing model biases and maintaining data protection and confidentiality.
Responsible AI techniques should remove biases ingrained in the models that fuel it, in addition to ensuring data security. Businesses should routinely assess any bias that may exist in the vendor’s models before recommending the best technology to customers.
Companies can attempt to reduce adverse effects even if they cannot completely eliminate the biases included in AI systems that have been trained on vast amounts of data. Here are a few recommendations:
Humans should still come first even though Artificial Intelligence can help reduce the amount of repetitive work that needs to be done by them. Businesses must foster a culture that rejects the idea that AI and people are either/or options. It’s critical to leverage the creativity, empathy, and dexterity of human teams while allowing AI to increase productivity.
There are many foundation solutions or models that can be applied without training data; however, in some circumstances, the level of accuracy could be significantly higher. The best outcomes will come from tailoring AI systems to the business objectives and data. When done effectively, data cleaning and preparation can eliminate biases in this step. The development of ethical AI solutions depends on eliminating bias from data.
Organizations must commit to safeguarding every piece of data they gather, no matter how much of it they acquire. Working only with third-party providers who completely adhere to the requirements set forth in important pieces of legislation, such as GDPR, and who maintain essential security certifications is one approach to do this. Although they require a lot of work, observing these laws and obtaining these certifications serve as proof that the company is capable of protecting consumer data.
Once a system is in use, it is critical to obtain human feedback on its effectiveness and biases. In the event that users notice that the result varies based on the scenario, it is crucial to establish guidelines for reporting and to resolve the problem. This can be done as an output correction at the core of the AI system.
Partners and customers will demand it as more companies adopt company language related to ethical and responsible Artificial Intelligence.
Additional support is essential when one error can cost the company millions of dollars or destroy its reputation and relationships with customers and employees. Nobody wants to work for a company that deploys discriminatory Artificial Intelligence solutions or carelessly handles customer data. Consumer trust will increase, and the advantages of using AI will become more apparent the sooner the company addresses these problems.
Check Out The New Enterprisetalk Podcast. For more such updates follow us on Google News Enterprisetalk News.
Prangya Pandab is an Associate Editor with OnDot Media. She is a seasoned journalist with almost seven years of experience in the business news sector. Before joining ODM, she was a journalist with CNBC-TV18 for four years. She also had a brief stint with an infrastructure finance company working for their communications and branding vertical.
A Peer Knowledge Resource – By the CXO, For the CXO.
Expert inputs on challenges, triumphs and innovative solutions from corporate Movers and Shakers in global Leadership space to add value to business decision making.Media@EnterpriseTalk.com