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A common challenge with using artificial intelligence in the workplace is that many employees lack proper training to use AI effectively.
According to Microsoft’s and LinkedIn’s 2024 Work Trend Index on the State of AI at Work, released in May, only 39% of AI users receive workplace training. The report identifies four categories of workers: skeptics, reluctant users, poorly or untrained users, and power users. Read More
Artificial intelligence may be the next great thing for industry, but users still fear its shortcomings in business and digital testing.
While customer experience (CX) and quality assessment are radically different, the associated risks may extend beyond satisfaction alone. Outcries persist that AI-powered CX systems produce subpar results and threaten human agent jobs. Read More
Data poisoning is a cyberattack where adversaries inject malicious or misleading data into AI training datasets. The goal is to corrupt their behavior and elicit skewed, biased, or harmful results. A related danger is creating backdoors for malicious exploitation of AI/ML systems. Read More
