The future of artificial intelligence
人工智能正在进入第三次浪潮，机器可以评估数据的背景，从而做出自己的决定. What new abilities can come from this and are there any pitfalls? In the 零压力 podcast, 我们的主持人Helen Sharman与专家Tero Ojanperä和Karen Haigh博士一起讨论人工智能第三波的影响.
教育, 更大的透明度和信任是广泛接受人工智能(AI)第三波浪潮的关键, 根据我们在帝国理工学院和十大正规博彩网站排名的第三集的两位人工智能专家的说法 零压力 podcast.
Both Tero Ojanperä, the co-founder of Silo, the Nordic Region’s largest private AI lab, and Dr Karen Haigh, an expert in cognitive techniques for physically-embodied systems, are convinced of the benefits more advanced AI capabilities can offer.
然而，他们也告诉播客主持人海伦·沙曼(Helen Sharman)，他们同样确信，我们必须清楚这项技术是如何以及为什么这样运作的, neither dismissing nor unthinkingly accepting it, and that we must take charge.
“作为人类，我们必须能够给它设定适当的界限，”黑格博士说.
“It’s not unlike what you would do with your toddler at home. 你在孩子周围设置了栅栏，以确保他正在学习你想让他学习的东西.”
Advanced capabilities, great potential
AI has been around since the 1950s, 在20世纪60年代扩展到机器学习之前，它从简单的统计过程开始. However, in the past decade it has been developing at breakneck speed.
第三波人工智能浪潮承诺，机器可以将数据点置于情境中. “Something we as humans do all the time, for example when understanding what a road sign means, even when it’s covered in dirt and hardly visible,” says Helen Sharman. 例如，我们已经看到这种类型的人工智能进入自动驾驶和辅助驾驶汽车.
Tero Ojanperä和Karen Haigh博士都认为，这一新的人工智能浪潮在许多应用中具有巨大的潜力, including school education, supply chain management and coordinating responses to natural disasters.
“这不是关于人工智能接管，而是关于人工智能在日常工作中支持人们, 帮助解决大问题，从而使世界变得更美好. It’s about rethinking how we perceive AI,” says Ojanperä.
“当我们考虑教学过程时，人工智能可以在数字环境中收集学习数据. You can see better who’s falling behind and give them individual support. And AI can interact when it comes to teaching. It can be the teacher on many occasions, 就像我们在客户服务应用程序中使用的聊天机器人一样.”
The keys to realising AI’s promise
As befits a technology now enabling machines to contextualise data, 我们的专家认为，将人工智能融入到我们的生活中是关键. Neither see it as a risk to humanity.
黑的博士, who has written about the role of AI in electronic warfare, 认为该技术非常适合在有限情况下快速处理复杂任务, such as the battlefield.
“If we are looking at a critical defence sector, situations with hard real-time operating constraints, things must happen in very tight time frames. You’re operating with small embedded devices. You can’t go back to the cloud to do the huge computations. There’s a need for the right decisions to be made quickly,” she explains.
“军事情况的另一个主要区别是，通常没有以前的学习例子. You’re doing real-time, 在任务中学习，有些系统会在没有数据的情况下离开. 火星探测器没有时间返回地球，因为它做出了每一个决定. AI is just a tool, like a set of mathematical tools that can be applied to problems, and it’s especially useful in remote and rugged environments.”
Tero Ojanperä补充道:“人工智能有很多好处，但我们对人工智能保持透明是非常重要的, 不仅是在教育领域，如果人们在客户服务中与聊天机器人交流，如果你认为它是人类，然后发现它是人工智能，你可能会生气或失望. 这一切都是为了保持透明，用简单的语言解释它是如何工作的.”
And for both experts, informed trust is crucial.
“如果我们考虑有车道跟踪和巡航控制的汽车，我们一直接受它们, so it’s building up trust in AI from the lowest level,黑格博士说.
“AI is still like a human. It makes mistakes sometimes,” adds Ojanperä. “如果我知道它可以控制汽车，但我仍然需要保持警惕，这是可行的. 只要我们不盲目信任，保持透明，世界就是我们的.”
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