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SMF Coding Discussion / To get value from AI, what’s one thing that leaders can start doing today
« เมื่อ: 7/02/23, 10:28:00 »
To get value from AI, what’s one thing that leaders can start doing today that doesn’t take big effort or money
Who doesn’t love simple hacks that can be done today with little effort? Experts opine that organizations will benefit by defining the real business purpose of AI. They can save time by doubling down on data quality before spending boatloads of money on models. ChatGPT recommends leaders educate themselves on AI and its risks to make informed decisions about deploying it.
Start brainstorming about the particular business use cases in your organization that can benefit from massive amounts of data to assist in day-to-day tasks. Remember, AI is good at recognizing patterns, and humans are good at understanding when those patterns have meaning versus when they are spurious correlations. - Ngan Khanh Nguyen MacDonald
Often, many leaders hire the team first and then try to figure out what they'll do. That just doesn't work. While developing our strategy at Janssen, we think about the questions to pursue and prioritize them based on two factors - business importance and data science feasibility. Focusing on the prioritized list of initiatives helps deliver impact, secure buy-in, and build the organizational momentum to do more. That’s what I did at J&J two years ago as a new emerging leader. By reviewing our program pipeline, I picked the priority areas to apply data science. For some programs, it was accelerating trial recruitment, whereas in others, it was finding more precise endpoints to measure patient outcomes better. This helped us figure out the top ten programs to go after. - Najat Khan
Dive deeper into your existing data. Focusing on data initiatives such as data sampling, data augmentation, and training procedures can lead to outsized gains in AI performance. It does not require acquiring more data or investigating a new model architecture. - Alex Lang, vice-president of Technology of Unlearn
Leaders need to align and educate – the only cost in doing so is time. One of the main obstacles to mass AI adoption in healthcare is building trust and educating on what AI can and cannot do. AI should be marketed responsibly or risk being perceived as immature or overhyped. We are tackling this challenge head-on through a society that aims to provide professional leadership in the provisioning and regulation of AI in fertility. - Eran Eshed
Educating themselves about AI: One of the most important things that leaders can do is to educate themselves about the capabilities and limitations of AI, as well as the potential benefits and risks associated with its use. This can help leaders to better understand how AI can be used to support their organizations and to make informed decisions about its adoption and deployment. - OpenAI ChatGPT
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Who doesn’t love simple hacks that can be done today with little effort? Experts opine that organizations will benefit by defining the real business purpose of AI. They can save time by doubling down on data quality before spending boatloads of money on models. ChatGPT recommends leaders educate themselves on AI and its risks to make informed decisions about deploying it.
Start brainstorming about the particular business use cases in your organization that can benefit from massive amounts of data to assist in day-to-day tasks. Remember, AI is good at recognizing patterns, and humans are good at understanding when those patterns have meaning versus when they are spurious correlations. - Ngan Khanh Nguyen MacDonald
Often, many leaders hire the team first and then try to figure out what they'll do. That just doesn't work. While developing our strategy at Janssen, we think about the questions to pursue and prioritize them based on two factors - business importance and data science feasibility. Focusing on the prioritized list of initiatives helps deliver impact, secure buy-in, and build the organizational momentum to do more. That’s what I did at J&J two years ago as a new emerging leader. By reviewing our program pipeline, I picked the priority areas to apply data science. For some programs, it was accelerating trial recruitment, whereas in others, it was finding more precise endpoints to measure patient outcomes better. This helped us figure out the top ten programs to go after. - Najat Khan
Dive deeper into your existing data. Focusing on data initiatives such as data sampling, data augmentation, and training procedures can lead to outsized gains in AI performance. It does not require acquiring more data or investigating a new model architecture. - Alex Lang, vice-president of Technology of Unlearn
Leaders need to align and educate – the only cost in doing so is time. One of the main obstacles to mass AI adoption in healthcare is building trust and educating on what AI can and cannot do. AI should be marketed responsibly or risk being perceived as immature or overhyped. We are tackling this challenge head-on through a society that aims to provide professional leadership in the provisioning and regulation of AI in fertility. - Eran Eshed
Educating themselves about AI: One of the most important things that leaders can do is to educate themselves about the capabilities and limitations of AI, as well as the potential benefits and risks associated with its use. This can help leaders to better understand how AI can be used to support their organizations and to make informed decisions about its adoption and deployment. - OpenAI ChatGPT
เปิดยูสเล่นยูฟ่าเบท
