Kori Schake

It's too soon to tell, because we're at the early stage of what the people who understand the technology best are telling us is going to be a bigger economic and social upheaval than the industrial revolution. The industrial revolution took about 100 years before the social and political and economic effects were really fully evident. It's too soon to tell.

It's also a pleasure to be on with Audrey Tang, who I admire enormously and would defer to her answers on these things. But my sense is that there's a two-stage battle going on. One line of effort is the countries that are pushing the frontier of the development of the technology.

And there, it does really matter who's first, because it looks like a first-mover advantage will drive the frontier forward in potentially different directions and will have enormous national security consequences. I mean, even if you just look at the way artificial intelligence is changing military operations and intelligence practices by allowing the assessment of enormous pools of data, so making things more transparent, easier to target. But you can also see that that doesn't add up to winning wars.

So it's early on in the development. But the second track, I think, which goes to the latter part of your question, Jean-Marie, is that it's not clear the first-mover advantage of people at the frontier are going to be how artificial intelligence is adopted across economies, across states, across political communities. And there, it looks to me that the first-mover advantage might actually be detrimental because lesser models can use the data pools that the frontier organizations have developed and create solutions to problems that are plenty good for what is needed in that space.

So I think it's too soon to tell, but there look to be enormous advantages on the frontier for being a technological leader. And it's not clear that those advantages will pertain across broad-scale adoption.

So I think artificial intelligence is changing some of the tradecraft of national security because it's harder for spies, for example, to have unsupervised engagements, right? It's increasing the transparency both on the battlefield and its increasing search capability. So you can, you know, if an intelligence agency records every foreign telephone call, the constraint isn't on the recording, it's on the processing of information, people to listen to it and identify where there are patterns.

And artificial intelligence is genuinely brilliant at that work. Just to take one small example, I was on the historian advisory committee to the State Department and we did a test run on whether using artificial intelligence to evaluate freedom of information document releases could assist. Would it increase the need for human supervision?

Would it reduce? And what we found is that it takes away the majority of cases which are easy to solve by a decision rule. And that freed up the actual talented people to focus only on the hard cases.

And so it didn't so much reduce the need for human labor as focus the need for human labor on the most intellectually challenging elements of the problem. So that's one, I think, really valuable test case. And as Emmanuel said, I can see a thousand applications in the healthcare sphere for that, identifying new vaccines or new treatments or solving difficult problems that a decision rule can solve for you, but it can't substitute for judgment.

And so in warfare, identifying where things are on a battlefield, both for situational awareness and for targeting is an enormous advantage. And if those targets are targets that don't require human judgment, right? Every tank moving on a battlefield, every enemy tank moving on a battlefield should be targeted.

That doesn't require human judgment unless you are worried about your munitions stockpiles, in which case you can also put in an algorithm to prioritize certain types of targets or locations. But what it cannot do for you is say, should I do this? That's a fundamentally human decision-making.

And in warfare, that's really important decision-making. Back in the 1990s, the Commandant of the Marine Corps, General Charles Krulak talked a lot about what he called the strategic corporal, which is the lowest ranking soldier on the battlefield can make a choice that will have strategic implications. And there's no amount of automation that can prevent bad human choices in conflict situations and can replicate good human choices.

So what is changing, I think we are seeing is the persistent surveillance at low cost that drones either relying on a communications network or independently targeted. That has reduced the ability of mobility on the battlefield. It's reinforced the advantages of defenders over the prospects of attackers.

That's a legitimate change. The second legitimate change of what's happening as a result of artificial intelligence is it's so easy to print low cost drones. And if you don't care whether 947 of a thousand get destroyed, then you can have enormous effects.

So the cost effectiveness, it used to be, you had to be a great power to afford persistent surveillance on the battlefield. That's not true anymore. And so that's an advantage to insurgents.

It's an advantage to terrorist organizations. It's an advantage to countries of the Global South in defending themselves against higher capability militaries. So I think it's changed those things, but what it hasn't changed is the grit of societies refusing to accept bad outcomes and other fundamentally human judgments on which winning and losing wars continues to rely.

I got nothing to add, Jean-Marie.

Sorry. Okay. I think I actually got a pass.

I don't think any of those questions were directed at me. So I will give my time to my co-panelists.

現在下結論還為時過早，因為最了解這項技術的人告訴我們，這將是一場比工業革命更巨大的經濟與社會劇變，而我們目前仍處於初期階段。工業革命花了大約一百年，其社會、政治與經濟影響才真正完全顯現。現在判斷確實言之過早。

同時，能與我極為欽佩的唐鳳同台 也非常榮幸，在這些問題上我更想聽她的見解。但我個人的感覺是，當前正在進行一場兩階段的博弈。第一條戰線是推動技術發展前沿的國家。

在那裡，誰先拔得頭籌確實至關重要，因為先發優勢似乎會推動前沿朝著潛在不同的方向發展，並帶來巨大的國家安全後果。我的意思是，即使你只看人工智慧如何透過評估龐大的資料庫來改變軍事行動和情報實務，讓戰場變得更加透明、更容易鎖定目標；但你也可以看到，這並不等於就能打贏戰爭。

因此，目前的發展仍處於早期階段。但第二條軌道——我認為這觸及了你剛才問題的後半部分，Jean-Marie——那就是目前尚不清楚前沿開拓者的先發優勢，是否能決定人工智慧在跨經濟體、跨國家、跨政治社群中的普及方式。在我看來，先發優勢甚至可能產生不利影響，因為較次級的模型可以利用前沿機構開發出的資料庫，針對該領域的需求創造出相當夠用的解決方案。

所以我覺得現在說還太早，但作為前沿的技術領導者顯然擁有巨大優勢；只是這些優勢是否能在廣泛普及的過程中延續下去，目前還不得而知。

我認為人工智慧正在改變國家安全領域的某些專業手法，例如間諜越來越難進行無人監控的接觸，對吧？它提高了戰場的透明度，也增強了搜尋分析能力。如果情報機構錄下了每一通境外通話，瓶頸不在於錄音本身，而在於資訊處理——需要有人去聽並找出其中的模式。

人工智慧在這類工作上表現確實極為出色。舉個小例子，我曾任職於美國國務院歷史文獻諮詢委員會，我們曾進行過一項測試，看看利用 AI 評估資訊自由法案（FOIA）解密文件是否有所助益。這會增加還是減少對人工審查的需求？

結果我們發現，AI 處理掉了大部分依循既定規則即可解決的常規案件。這讓真正有專業能力的人員得以專注於棘手案例。

因此，它與其說是減少了對人力的需求，不如說是將人力集中在問題中最具智力挑戰的部分。我認為這是一個非常有價值的測試案例。正如 Emmanuel 所說，在醫療領域同樣能看到上千種此類應用，例如辨識新疫苗、新療法，或是解決規則足以應對的難題；但它無法取代人類的判斷。

在戰爭中，無論是為了掌握戰場態勢還是鎖定目標，辨識戰場物體的位置都具有巨大優勢。如果那些目標是不需要人類複雜判斷的目標——戰場上移動的每一輛敵方坦克都應該被鎖定打擊。

這不需要人類判斷，除非你擔心彈藥庫存不足，在這種情況下你也可以設定演算法來排定特定類型目標或地點的優先順序。但它無法替你回答：『我究竟該不該這樣做？』這本質上是人類的決策過程。

在戰爭中，這是至關重要的決策。早在 1990 年代，美國海軍陸戰隊司令 Charles Krulak 將軍就曾詳盡闡述過所謂的「戰略下士」（strategic corporal）概念——戰場上階級最低的士兵所做的抉擇，也可能產生戰略層面的重大影響。任何自動化技術都無法阻止衝突環境中糟糕的人類抉擇，也無法複製優秀的人類決策。

因此正在發生的轉變是：依靠通訊網路或自主鎖定目標的低成本無人機帶來了持續性監控。這降低了戰場上的機動能力，增強了防守方相對於進攻方的優勢。

這是實質的轉變。由 AI 帶來的第二個實質轉變是製造低成本無人機變得極其容易。如果你不在乎一千架無人機當中有 947 架被摧毀，你就能產生巨大的打擊效果。

因此在成本效益方面，過去只有大國才能負擔得起戰場上的持續性監控，如今已非如此。這給了叛亂團體優勢。

這也給了恐怖組織優勢，給了全球南方國家在抵禦高軍事能力對手時的防衛優勢。我認為 AI 改變了這些層面；但它沒有改變的是社會拒絕接受惡果的堅韌意志，以及戰爭勝負所繫的其他本質上屬於人類的判斷。

我沒有要補充的了，Jean-Marie。

不好意思，我想我這次可以先略過。

我覺得剛才沒有針對我的具體問題，所以我把時間讓給其他與談人。