每日英語跟讀 Ep.K026: 學程式設計也可能會過時 Prepare for Change by Expecting the Unimagined

Self-driving vehicles could upend the transportation sector and eliminate a million or more jobs. Algorithms that decode MRIs put a whole medical subfield at risk. And the list of professions and sectors soon to be obsolete grows steadily by the day.

自駕車可能顛覆運輸部門，消滅一百萬個、甚至更多的就業機會。可為核磁共振攝影解碼的演算法，可能讓醫學的一整個區塊岌岌可危。不久即會過時的職業與部門，則在逐日穩定增加。

New technologies are rattling the economy on all fronts. While the predictions are specific and dire, bigger changes are surely coming. Clearly, we need to adjust for the turbulence ahead.

新科技正為經濟的各個領域帶來動盪不安。儘管這些預測明確又可怕，更大的改變仍然篤定會來臨。顯而易見，我們必須作好調整，以順應前方的湍流。

But we may be preparing in the wrong way.

不過，我們的準備可能錯了。

Both history and psychology tell us that our capacity to predict the future is limited, while our capacity to believe in such predictions is unlimited. We have always been surprised.

歷史和心理學兩者都告訴我們，人類預測未來的能力是有限的，然而人類相信這種預測的能力卻是無限的。一切總是出乎我們意料之外。

Rather than planning for the specific changes we imagine, it is better to prepare for the unimagined — for change itself.

與其為我們想像的特定改變預作計畫，不如為無法想像的作好準備，也就是為改變本身作好準備。

Preparing for the unknown is not as hard as it may seem, though it implies fundamental shifts in our policies on education, employment and social insurance.

為未知的變化預作準備，不如表面看來那般困難，儘管這意謂我們的教育、就業、社會保險政策必須作出根本的改變。

Take education. Were we to plan for specific changes, we would start revamping curriculums to include skills we thought would be rewarded in the future. For example, computer programming might become even more of a staple in high schools than it already is. Maybe that will prove to be wise and we will have a more productive workforce.

以教育為例。如果我們要為特定的變遷擬定計畫，就必須開始改革課程，將我們認為會在未來獲得回報的技術納入。舉例說，電腦程式設計在中學課程中可能成為比現今分量更重的主科。日後這可能會證明是明智之舉，而且我們會擁有生產力更高的勞動力。

But perhaps technology evolves quickly enough that in a few decades we talk to, rather than program, computers. In that case, millions of people would have invested in a skill as outdated as precise penmanship.

不過，科技演進的速度也可能快到幾十年內我們便可直接跟電腦說話，而不必再透過程式設計。果真如此，形同有數以百萬計的人投資在和精確書寫一樣過時的一項技巧上。

Instead, rather than changing what we teach, we could change when we teach.

此外，與其改變我們教導的「內容」，不如改變教導的「時間點」。

Currently, all the formal education most people will receive comes early in life. Specific skills may be learned on the job, but the fundamentals are acquired in school when we are young. This sequence — learn early, benefit for a lifetime — makes sense only in a world where the useful skills stay constant.

目前多數人是在年輕時接受所有的正規教育。特定技能可能就業後再從工作中學習，但是基礎教育都是年輕時在學校取得。早年學習，一輩子受惠的這種順序，唯有在有用的技能一成不變的世界才言之成理。

But in a rapidly changing world, the fundamentals that were useful decades ago may be obsolete now; more important, new essential skills may have arisen. Anyone helping a grandparent navigate a computer has experienced this problem.

在瞬息萬變的世界中，數十年前有用的基礎教育現在可能已過時；更重要的是，新的基本功可能已經出現。協助祖父母操作電腦的每個人都體會過這種問題。

Once we recognize that human capital, like technology, needs refreshing, we have to restructure our institutions so people acquire education later in life. We don’t merely need training programs for niche populations or circumstances, expensive and short executive-education programs or brief excursions like TED talks. Instead we need the kind of in-depth education and training people receive routinely at age 13.

一旦認清我們的人力資源和科技一樣需要更新，我們就必須重建機制，讓人們得以在年紀較大時受到教育。我們不僅須為利基族群與環境提供訓練計畫，昂貴和短期的高管教育計畫以及類似TED大會演講的簡短瀏覽。我們還需要人們照例會在13歲時接受的那種深度教育和訓練。

Source article: https://paper.udn.com/udnpaper/POH0067/318780/web/