#AI@Work: Only As Dependable As What’s Behind It
Now is the time to wake up! We need to get smarter about what’s happening with AI. AI now comes to us in the form of chips embedded in IOT using mostly speech recognition and natural language processing. It is in your car, refrigerator and light fixtures. It is part of your surveillance cameras and part of your email inbox. AI has a positive and negative side. The positive side will help us live smarter, work smarter and create healthier and safer work environments. But the potential for hacks, malicious use and abuse are real. AI has and will continue to disrupt all industries. It will affect the workplace locally and globally. There is no doubt unemployment will increase and no doubt that AI will make our lives easier.
Automated application development has gone mainstream. AI meets DevOps (Development and Operations). Data is created by using AI technologies. Quality is taking the place of sheer quantity with the data provided for AI. Companies are springing up with the sole purpose of cleaning up unstructured “Big Data” and making it into more usable “Little Data.” Natural language processing has made it easier for machines to talk to humans and humans to talk to machines. Building on these capabilities, computers can discern understanding, and capture sentiment, meaning and intent. By combining what computers do best (machine learning, deep learning, language processing, understanding, forecasting and optimization), the reach of AI continues to grow. AI can chart changes in account spending or forecast energy consumption or weather patterns. AI is getting better and better. We use it to classify, group and arrange data about everything. AI helps us understand X-rays and can determine if the nodes on a scan are benign or malignant. AI can transcribe speech to text. AI offers us shopping suggestions, generates reports and summarizes results. All AI requires data. AI is only as good and dependable as the programming that went into it and the data that supports it.
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