I am an entrepreneur and technologist in the AI space and the CEO of AIClub and AIClubPro, pioneering AI Literacy for K-12 students and individuals worldwide (https://corp.aiclub.world and https://aiclubpro.world). I am also the author of Fundamentals of Artificial Intelligence, the first AI textbook for middle and high school students.
The AI wave has come on faster than most expected. Over the last decade, companies have slowly but surely started deploying AI. Return on Investment was beginning to turn positive. Then ChatGPT arrived, and suddenly AI was everywhere.
If a company thought AI was critical to its future before, it has now acquired a new sense of urgency far beyond what it previously had. That said, just because something sounds urgent does not make it any easier for an organization. Some factors make adoption easier, but the urgency does not translate into a similar ease of implementability. In particular, if an organization does not have a solid data practice or data governance policy - can it do AI? This is a challenging question. On one hand, the easy answer is data has to come first. AI relies on data, and bad data leads to bad AI or worse, legal and other problems if bad data is used to make problematic AIs. On the other hand, at the pace at which AI is moving, can an organization really say no AI at all till they have achieved acceptable data practice and data governance across every aspect of their business? What would the opportunity cost be? And when would the data strategy be acceptable enough? As AI changes, will the needs of the data strategy also change? As in many cases, the easy answers are all insufficient . Good data practice cannot be ignored, and AI cannot wait. So what is to be done? Some ideas followThis is good practice regardless of where your data strategy and data readiness are at. AI that delivers good ROI starts with a focus on the problem, not the AI. The questions you should ask yourself are: Why do I believe AI will generate ROI and solve this problem better than it is solved in my business today? Does the answer to this depend on the data I have in-house? Often the answer is yes but sometimes the answer is no. For example - if you license an AI tool to help your employees write better reports, that may not require any or much custom data on your part. If your data strategy needs work, you may benefit from prioritizing work on your data strategy while leveraging AI options that add value to your business but do not require your in-house data. If the answer depends on the data I have in-house, what is the state of the data? What do I need to do to get it into a state that can support AI to success? What best practices can I put in place along the way for this data that I can also leverage elsewhere? If I am convinced of the above, does my organization understand that the data practice and the AI practice have to evolve together? Is it clear to my stakeholders that putting the AI ahead of the data is likely to fail, but if properly executed, all data for all use cases does not have to come ahead of AI for a particular use case? Do I have an organization in place that can orchestrate this workflow? Does my organization understand that, even if the AI does not require in-house data, there can be data practices associated with the AI? For example, if you leverage a third party AI tool to help your employees write reports, do they understand what information they are allowed to give this AI and what guarantees they have of privacy or other protection? Even if the AI is as simple as a grammar checker - these are serious questions that can impact your business.If you have any doubts about the quality of your data, fix those before investing in AI. Bad data always leads to bad AI. Do not let the AI create any data-related ethics violations, such as bias or privacy issues. Follow good data practices as you develop and deploy your AI. Some example guidelines can be found Make sure that any data you use to build or optimize your AI is protected from theft and loss. Once an AI is built, you should expect to train it again and again. Loss or damage to the data will then damage a launched product or AI development investment. The pace of AI evolution is fierce. There is unfortunately not much opportunity to wait till all dependencies are fully met. However, organizations that do not have their data practices in good shape will lose out on AI in the long run, and organizations that have solid data practices will have an advantage with AI. If possible, thread the needle and get both done.Our community is about connecting people through open and thoughtful conversations. We want our readers to share their views and exchange ideas and facts in a safe space.Insults, profanity, incoherent, obscene or inflammatory language or threats of any kindContinuous attempts to re-post comments that have been previously moderated/rejectedAttempts or tactics that put the site security at riskProtect your community.
Ai Ai Strategy Data Strategy Ai For Business
United States Latest News, United States Headlines
Similar News:You can also read news stories similar to this one that we have collected from other news sources.
Quest for Data-Driven Innovation: Blockchain-based Data Offers New OpportunitiesHere’s how blockchain systems can address major challenges in data usage in tech
Read more »
The world's first airport to require biometric boarding is set to arrive in 2025The UAE's plan to use end-to-end biometric boarding by next year is being cheered by tech proponents, travel experts and Elon Musk.
Read more »
'Israel's Starvation Strategy': IDF Fires on World Food Program TeamJake Johnson is a senior editor and staff writer for Common Dreams.
Read more »
World Health Organization unveils global strategy to contain mpox outbreaksRooted in fact-based, transparent reporting, Newsy is an award-winning opinion-free network owned by the E.W. Scripps Company that is relentlessly focused on “the why” of every story and seeks to enable a more intimate and immersive understanding of the issues that matter.
Read more »
New Study Backs Simple Weight Loss Strategy That Doesn't Require DrugsThe Best in Science News and Amazing Breakthroughs
Read more »
Anchorage will require market data from short-term rental platforms like Airbnb and VrboThe Anchorage Assembly’s measure calls for short-term rental online platforms to give the city information on the numbers of rentals, their locations and the types of units rented, among other information.
Read more »