AI has worked its way into the fabric of our daily life. It’sused casually within smart home devices like those produced by Google, Amazon, and Apple – much like that found in smartphone devices and soon in vehicles. Getting within the home is usually the ultimate goal, but it is already there. Can it do more? Of course. It is still convenient and useful, as it is, but, obviously, there is the assumption that AI will have more autonomy, or at least relieve humans of more tasks than it currently is doing. This development will come from those businesses and individuals who have their sights set on products that will offer in-home assistance. However, there are other products and industries where AI is finding huge use and disrupting established and traditional norms which will feed into the push for AI’s higher functioning. Here are a few examples of where it’s making serious waves.
Captioning and Transcription
AI is helping communication by changing the transcription and captioning services. Speech-to-text practices have been historically completed by the human hand. Now, with acoustic and linguistic models which enable a representative relationship between the audio and words themselves so they can be deciphered and transcribed into coherent and grammatical logical sentences. These services are used for pre-recorded and live content. It is the live content that is where the disruption to the industry occurs. The integration with Zoom for business conferences or lectures, for instance, enables more people to access content in these small environments with huge expenses on either human transcribers or sign-language translators (which aren’t always necessary). YouTube (AI can help improve creator’s videos too) has their own transcription service for video on their platform but they aren’t well received at all – especially after removing their Community Contribution feature – and are often flawed. However, with improvements by other firms, major platforms like YouTube and Twitch could internalize the software and make captioning software in particular widespread.
Insurance companies like Lemonade use AI. One of its biggest benefits is that it helps resolve claims quicker and, therefore, reimburses much faster than other companies. The AI is trained with machine learning – so understands the various categories and variables through which claims are processed. It can then “make decisions” based on new claims almost immediately handling multiple claims at a time. In some cases, Lemonade’s customer experience team will review it but more often than not the AI can handle it. Additionally, this means there’s less overhead for the insurance company and, can, therefore, provide a competitive insurance quote.
There could come a point in the near future where patients will attend an appointment at a hospital – general, eye, women’s, any hospital – and be met and seen-to by an AI. Even now, AI matches and outperforms medical professionals’ ability to diagnose patients and provide medical advice. Patients are still not convinced by them. Studies suggest that it’s because patients believe their medical needs are unique, outliers to the data which provides the AI’s knowledge. It could well be a matter of time: at some point, it’ll be impossible to deny AI’s effectiveness. The other option could be figuring out how to communicate the AI’s diagnosis. It won’t be that patients sit in a photo-booth sized pod to receive difficult news on a screen, but having some finesse will be important.
AI can help save money in various areas of the medical sector too. In pharmaceutical development, AI will make the whole process more efficient, by eliminating dead-ends and finding more likely and more effective solutions that human scientists cannot foresee, and dealing with large amounts of data in shorter and shorter periods of time.
Some sports – clubs/franchises, associations/governing bodies, and broadcast teams – are slower to embrace new technology and ideas than others. Soccer has been notoriously slow to embrace data analytics and has only just implemented video-replay systems to help on-field referees make correct decisions. AI has slowly made its presence known in sports like baseball, basketball, and football. Its use in data analysis before the game has enabled baseball coaches to decide the batting order which will enable them to capitalize on their opponent’s weaknesses. Post-match, a similar thing can be achieved with improvements to be made. There are even in-game benefits, such as football coordinators and head coaches running plays which the AI has suggested, based on what’s been happening in the game so far.