It is overwhelming when technology seems to be ahead of many organizations, or at least this is what worries them. Every day new techniques or new artificial intelligence models appear, ranging from those that help in sales prediction, or in customer service with chatbots (which many of us have probably already used), to quality control in manufacturing. Organizations are also struggling to gain a deeper understanding of how these complex AI systems work and how they can implement them in their database.
At AI Transform LLC we work every day to clarify so many myths about AI and, more importantly, to help organizations exploit AI in a transparent and ethical way. AI was made to be leveraged, not feared; however, here are some of the concerns organizations face and how they can be addressed.
1. Replacement of Employees by AI
The implementation of AI to streamline tasks worries employees because they tend to think that it can replace them, which can cause them stress at work, reduce their productivity and performance. This concern may be mostly present in the area of customer service because AI can address routine questions.
2. Lack of Transparency
These artificial intelligence models operate as “black boxes” because of their complex way of understanding their decision making process. This raises doubts in areas such as finance or law where it is crucial to obtain fair and sensible answers.
3. Unclear Responsibility
In the event of issues arising as a result of AI-driven decisions, who is really responsible?
4. Content Authenticity
Distinguishing between content created by artificial intelligence and content created by a human being has become a challenge. This can lead to fake content that could spread false information or affect the reputation of companies.
5. Copyright Concerns
AI systems trained on publicly available text may create content very similar to published works. This raises questions about copyright issues and creates potential legal problems.
Here’s how to address these concerns:
1. Reskill Workforce for AI Integration
Companies adopt AI to team up with employees not replace them. Additionally, new positions focused on overseeing AI performance can be created.
2. Improve Understanding
To increase the reliability in AI decisions, AI explainability initiatives should be adopted. Techniques such as SHAP, partial dependence diagrams or LIME, among others, could be used to achieve such explainability. Supporting initiatives that allow people to see how systems work and creating dedicated teams to test the fairness of AI systems can also contribute to the understanding of AI.
3. Maintain Human Supervision
AI must support decisions, not make them independently. Human supervision remains essential throughout the entire process, from data collection to training the models and evaluating the results.
4. Prevent AI-Generated Misinformation
Companies can combat fake content by developing tools to detect AI-generated material and implementing fact-checking systems. Digital watermarking can be an option to distinguish between real and AI-created content.
5. Address Copyright and Plagiarism Issues
Training artificial intelligence to generate a response along with the link or resource from which the information was obtained can avoid copyright issues and, at the same time, protect intellectual property.
Conclusion
AI should be viewed as a powerful tool to achieve great results, not as a source of fear or concern. With the right training, oversight and ethical integration, companies can use it to their advantage. Companies that embrace AI drive innovation and gain a clear competitive advantage.