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第17版| 2021年8月

Artificial intelligence and machine learning: Augmenting the future of business, 创造力和创新

即使在充满挑战的经济环境中, companies are pouring investment into artificial intelligence and machine learning projects in the hope of gaining critical business insights, 或者保持领先竞争对手一步. Yet evidence shows this spending doesn’t always drive value, or the desired results. The typical firm will wait months, even years, to see payback on an ROI project.



来源:ESI ThoughtLab


在本期《宝博体育官网》中, Thoughtworks’ experts unpack techniques and practices to help ensure AI is not just capable of delivering return on investment, but also contributes to the organization’s strategy and innovation portfolio.



i. 识别人工智能机会并采取行动


人工智能从未如此强大过, or more accessible - but that doesn’t mean it’s always the right solution to a business challenge. Understanding the best general use cases for automation, identifying specific processes that are ripe for improvement, and careful planning and testing should all be part of an evaluation that precedes any major AI plunge.


“More often than not, AI is a distinctive tool looking for a problem. People have spent a lot of money trying to do something they thought was the right thing and it didn’t work. That doesn’t necessarily mean the technology is wrong - it might just be that it’s being misused.”




A convergence of technology forces lays the foundation for AI to shine

Diagram of the convergence of technology forces laying the foundation for AI to shine


ii. 从自动化到增强——还有创造力 


自动化是AI/ML实践的标准目标, but is in fact just one aspect of a much broader potential value chain. By graduating from automation to augmentation companies can reap gains that go beyond productivity and efficiency. 最好的, AI becomes a tool to help organizations solve complex problems, 基于实时数据进行预测和调整, 甚至创造新的产品或业务线. 





3. 导航数据、人类和伦理维度


Building a successful AI practice for the long term requires organizations to manage three key challenges:


数据: 如果数据源是不同的, 扭曲或不可用, AI systems can generate incomplete or problematic outcomes that spiral into major issues, as machines learn based on previous faulty conclusions. 有时最好的方法是重新开始.  



"It can be easier to get started with real-time insights than historical data because the solutions are typically more lightweight. The idea is to try out different things, and see what works and what doesn’t…. 以应对快速发展的趋势.” 


Principal Consultant at Fourkind, part of Thoughtworks



人: 人工智能项目不可避免地涉及到人类角色, and those impacted need a say in how they’re rolled out and a degree of education to secure the necessary organizational buy-in. Broad-based support is vital in AI implementations because organizations are likely to find themselves short of dedicated talent.



来源:O ' reilly


道德: Allowing systems to make decisions like who gets access to a product or service, or when an image or interaction presents a possible problem, means these systems may have direct ethical implications. That puts the onus on the business to ensure AI-driven decisions are transparent, 可追踪的, 并且尽可能不带偏见.



“尽最大可能, you want people involved who have different views of the system, and different intersection points with the system or with the data. You want some people who are very familiar with how it’s supposed to work, and you also want people who are familiar with the consequences.”






人工智能是一个快速发展的领域, 拥有前所未有的计算能力, tailored algorithms and natural language processing all set to extend the frontiers of what’s possible for businesses. Enterprises can look forward to AI playing a more strategic and creative role as the age of augmentation arrives in earnest. At the same time, t在这里 are tasks that no system can take over.


“强化学习真的没有得到充分利用, but it’s going to be the biggest thing since the AI hype started in two to five years. The idea is that you don’t take all your past data and depend on that, but create an agent that takes actions and learns from the feedback in real time, 完全自主.”


Principal Consultant at Fourkind, part of Thoughtworks



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