查爾斯?勞曾經于美國空軍預備役部隊服役超過38年,當前正在現役部隊中擔任軍士長的職務,他打算退役后在地方找一份工作,但考慮到上一次在地方上求職已經是19年前的事情,他對自己能否如愿以償感到非常忐忑。
在談及求職時,勞說:“找工作不是一件容易的事情。首先,要想好自己下一步做什么,然后還得學著跟地方單位打交道,畢竟在軍中待久了,行事方式多少會與地方上有些差異。”
勞還說,他發現自己聽不太懂公司雇主使用的術語。“地方上用的術語和行話跟部隊里不太一樣,要弄明白雇主想要什么樣的人,并讓他們明白我有哪些技能需要費些功夫,而且讓雇主理解這些技能跟地方工作有什么關聯也不太容易。”
每年約有20萬軍人從軍中退役,回到地方生活,很多人面臨著和勞相同的困境。但從明年開始,一個基于人工智能的全新軟件系統將在求職方面為許多退役軍人提供幫助。
為幫助退役軍人更好地適應地方生活,找到適合自己的工作,美國勞工部(U.S. Department of Labor)推出了“過渡援助計劃”(Transition Assistance Program),為進一步改進該計劃,勞工部還舉行了一場軟件系統開發大賽。在此次比賽中,總部位于加州山景城、成立已經有四年的Eightfold AI公司脫穎而出,憑借基于人工智能技術開發的招聘與“人才管理”軟件一舉擊敗了50多家競爭企業,其中不乏領英、Vantage Point Consulting等招聘行業巨頭,甚至連專門幫助企業招聘退役軍人的JobPath Partners在其面前也敗下陣來。
Eightfold的公共部門業務高級總監丹?霍普金斯說,為了贏得這項比賽,公司專門為軍方人士創建了一個網站,將美軍職位代碼轉換為該職位所包含的各種技能,并加入了求職者可能具備的其他相關技能。同樣也是退役軍人的霍普金斯表示:“假設某人是一名炮兵,地方上能夠與之匹配的工作可以有什么?不過能夠肯定的是,從部隊出來的人都是久經考驗,并且擁有良好的領導才能。”
除了Eightfold,將人工智能技術用于招聘的初創企業還有數十家,包括Pymetrics、Mya Systems和HireVue等等。Eightfold的軟件能夠根據求職者的既有知識預測其未來可以學會哪些新技能。“如果你了解A技能,那么你就可能知道B技能,或者可以學會C技能,還能夠預測出你大概需要多久可以學會。”霍普金斯說。
Eightfold開發的這套系統可以對軍人的軍銜、級別以及他晉升到該級別的速度進行評估,這些信息能夠將候選軍人的領導能力和學習能力一目了然地呈現給雇主。“假設某位候選人只用五年時間就晉升到了上士級別,那說明他在部隊里的表現非常優秀,晉升速度很快。而在傳統的簡歷中,我們看不到這些信息。”
Eightfold的總裁卡邁勒?阿盧瓦利亞表示,退伍軍人擁有的許多軟技能在普通簡歷中并未得到體現,比如在不確定的環境中工作的能力。他說:“軍人擁有很多軟技能,而且他們還具備在高壓下工作的能力。”
霍普金斯表示,政府現有的“過渡援助計劃”項目的問題是,在了解求職者技能時過于依賴求職者填寫的自我評估問卷,搜索空缺職位也主要靠關鍵字搜索。但如其所言,許多退役軍人都低估了自己的實際技能,關鍵字搜索雖然可以幫助他們找到大量的潛在工作機會,但是卻沒有篩選最佳機會的好方法。以戰斗工程師為例,如果你是一位戰斗工程師,10月時在“過渡援助計劃”的職位數據庫中搜索華盛頓特區的空缺工程師職位,那么你會搜索到22,000多個可能的工作機會,從中進行挑選無疑是一項浩大的工程。
相比之下,Eightfold的軟件則為求職者提供了一份包含特定職缺的列表,還可以為雇主推薦合適的候選人。此外,該軟件還為職位相似或相關的退役軍人搭建了人脈網絡,同樣能夠為其所用。
霍普金斯說:“對處在過渡階段的軍人而言,搭建有質量、有相關性的人脈網絡非常重要。而我們所做的則是找到其適合的職位,再找出正在從事相關職位的退役軍人,并幫助他們建立聯系。”
在贏得本次比賽后,Eightfold拿到了72萬美元的獎金,同時還獲得了美國國防部與退役軍人事務部的支持。
即將退役的軍士長勞協助Eightfold完成了軟件測試工作,他表示,認識在潛在雇主處工作的退役軍人(在求職過程中)常常具有決定性意義。他說:“在公司里碰到退役軍人讓我感覺很舒服。作為軍人,無論是剛認識,還是已經有了多年的交情,我們對彼此都有一種家人的感覺。我也發現,退役軍人更容易理解彼此的想法。”
阿盧瓦利亞表示,該公司從各種公開及專有數據集中抓取了10億多名員工的個人資料,數據來源包括行業期刊上發布的招聘公告、校友雜志等處發布的文章、相關人員的晉升履歷等等,并用這些資料對Eightfold的人工智能系統進行了訓練,向其灌輸了超過50萬種職位及其對應的140萬項基本技能的相關信息。經過訓練之后,該算法將使用這些信息來嘗試預測給定求職者的職業發展道路。
Eightfold在上月的D輪融資中籌集了1.25億美元,使其自成立以來總的融資規模超過了1.8億美元。該輪融資由總部位于馬薩諸塞州坎布里奇市的風投公司General Catalyst領投,該公司對Eightfold的估值為10億美元。(財富中文網)
譯者:梁宇
審校:夏林
查爾斯?勞曾經于美國空軍預備役部隊服役超過38年,當前正在現役部隊中擔任軍士長的職務,他打算退役后在地方找一份工作,但考慮到上一次在地方上求職已經是19年前的事情,他對自己能否如愿以償感到非常忐忑。
在談及求職時,勞說:“找工作不是一件容易的事情。首先,要想好自己下一步做什么,然后還得學著跟地方單位打交道,畢竟在軍中待久了,行事方式多少會與地方上有些差異。”
勞還說,他發現自己聽不太懂公司雇主使用的術語。“地方上用的術語和行話跟部隊里不太一樣,要弄明白雇主想要什么樣的人,并讓他們明白我有哪些技能需要費些功夫,而且讓雇主理解這些技能跟地方工作有什么關聯也不太容易。”
每年約有20萬軍人從軍中退役,回到地方生活,很多人面臨著和勞相同的困境。但從明年開始,一個基于人工智能的全新軟件系統將在求職方面為許多退役軍人提供幫助。
為幫助退役軍人更好地適應地方生活,找到適合自己的工作,美國勞工部(U.S. Department of Labor)推出了“過渡援助計劃”(Transition Assistance Program),為進一步改進該計劃,勞工部還舉行了一場軟件系統開發大賽。在此次比賽中,總部位于加州山景城、成立已經有四年的Eightfold AI公司脫穎而出,憑借基于人工智能技術開發的招聘與“人才管理”軟件一舉擊敗了50多家競爭企業,其中不乏領英、Vantage Point Consulting等招聘行業巨頭,甚至連專門幫助企業招聘退役軍人的JobPath Partners在其面前也敗下陣來。
Eightfold的公共部門業務高級總監丹?霍普金斯說,為了贏得這項比賽,公司專門為軍方人士創建了一個網站,將美軍職位代碼轉換為該職位所包含的各種技能,并加入了求職者可能具備的其他相關技能。同樣也是退役軍人的霍普金斯表示:“假設某人是一名炮兵,地方上能夠與之匹配的工作可以有什么?不過能夠肯定的是,從部隊出來的人都是久經考驗,并且擁有良好的領導才能。”
除了Eightfold,將人工智能技術用于招聘的初創企業還有數十家,包括Pymetrics、Mya Systems和HireVue等等。Eightfold的軟件能夠根據求職者的既有知識預測其未來可以學會哪些新技能。“如果你了解A技能,那么你就可能知道B技能,或者可以學會C技能,還能夠預測出你大概需要多久可以學會。”霍普金斯說。
Eightfold開發的這套系統可以對軍人的軍銜、級別以及他晉升到該級別的速度進行評估,這些信息能夠將候選軍人的領導能力和學習能力一目了然地呈現給雇主。“假設某位候選人只用五年時間就晉升到了上士級別,那說明他在部隊里的表現非常優秀,晉升速度很快。而在傳統的簡歷中,我們看不到這些信息。”
Eightfold的總裁卡邁勒?阿盧瓦利亞表示,退伍軍人擁有的許多軟技能在普通簡歷中并未得到體現,比如在不確定的環境中工作的能力。他說:“軍人擁有很多軟技能,而且他們還具備在高壓下工作的能力。”
霍普金斯表示,政府現有的“過渡援助計劃”項目的問題是,在了解求職者技能時過于依賴求職者填寫的自我評估問卷,搜索空缺職位也主要靠關鍵字搜索。但如其所言,許多退役軍人都低估了自己的實際技能,關鍵字搜索雖然可以幫助他們找到大量的潛在工作機會,但是卻沒有篩選最佳機會的好方法。以戰斗工程師為例,如果你是一位戰斗工程師,10月時在“過渡援助計劃”的職位數據庫中搜索華盛頓特區的空缺工程師職位,那么你會搜索到22,000多個可能的工作機會,從中進行挑選無疑是一項浩大的工程。
相比之下,Eightfold的軟件則為求職者提供了一份包含特定職缺的列表,還可以為雇主推薦合適的候選人。此外,該軟件還為職位相似或相關的退役軍人搭建了人脈網絡,同樣能夠為其所用。
霍普金斯說:“對處在過渡階段的軍人而言,搭建有質量、有相關性的人脈網絡非常重要。而我們所做的則是找到其適合的職位,再找出正在從事相關職位的退役軍人,并幫助他們建立聯系。”
在贏得本次比賽后,Eightfold拿到了72萬美元的獎金,同時還獲得了美國國防部與退役軍人事務部的支持。
即將退役的軍士長勞協助Eightfold完成了軟件測試工作,他表示,認識在潛在雇主處工作的退役軍人(在求職過程中)常常具有決定性意義。他說:“在公司里碰到退役軍人讓我感覺很舒服。作為軍人,無論是剛認識,還是已經有了多年的交情,我們對彼此都有一種家人的感覺。我也發現,退役軍人更容易理解彼此的想法。”
阿盧瓦利亞表示,該公司從各種公開及專有數據集中抓取了10億多名員工的個人資料,數據來源包括行業期刊上發布的招聘公告、校友雜志等處發布的文章、相關人員的晉升履歷等等,并用這些資料對Eightfold的人工智能系統進行了訓練,向其灌輸了超過50萬種職位及其對應的140萬項基本技能的相關信息。經過訓練之后,該算法將使用這些信息來嘗試預測給定求職者的職業發展道路。
Eightfold在上月的D輪融資中籌集了1.25億美元,使其自成立以來總的融資規模超過了1.8億美元。該輪融資由總部位于馬薩諸塞州坎布里奇市的風投公司General Catalyst領投,該公司對Eightfold的估值為10億美元。(財富中文網)
譯者:梁宇
審校:夏林
Charles Law found the prospect of looking for a job daunting. After more than 38 years in the U.S. Air Force Reserve and then on active duty, Law, now a master sergeant, was retiring and looking for work in the civilian world. But it had been 19 years since he’d last searched for a job outside the military.
“It was kind of scary,” Law says of his employment search. “First trying to decide what it is that I wanted to do next and then having to deal with the civilian sector after having been attached to the military for so long.”
Law says he found the jargon used by corporate employers confusing. “The terminology and lingo is just not the same,” he says. “And trying to get an understanding of what they are looking for and trying to help them understand what skills I had and how that relates to a civilian job, that is a bit challenging.”
Each year, about 200,000 members of the armed forces leave the military and transition to civilian life. And many of them face the same struggles Law did. But starting next year, a new software system based on artificial intelligence will help many of these veterans find work.
Eightfold AI, a four-year-old company based in Mountain View, Calif., that makes A.I.-enabled recruiting and “talent management” software, won a U.S. Department of Labor competition to build a software system to help improve its existing Transition Assistance Program (TAP), which helps those leaving the military prepare for civilian life, including finding employment. The startup beat out 50 other companies, including more established players in recruitment technology such as LinkedIn, Vantage Point Consulting, and even JobPath Partners, a company that specializes in helping companies hire veterans.
To win the competition, Eightfold created a website for military members that takes a U.S. military job code and translates that job into its component skills—but also any related skills the job seeker might have, says Dan Hopkins, senior director of Eightfold’s public sector business. “If I am in artillery, what is the equivalent in civilian life?” Hopkins, himself a veteran, says. “But that person will have a lot of training and leadership skills.”
Eightfold is among dozens of startups—including Pymetrics, Mya Systems, and HireVue—that are applying A.I. to recruitment. The company’s software can predict what skills the job seeker might be able to learn based on what that person already knows. “If you know skill A, might you also know skill B or could you learn skill C, and how quickly could you learn it,” Hopkins says.
The system Eightfold built can also assess what rank and grade a person holds and how quickly they were promoted to that rank—which can be a good proxy for the ability to learn new skills and leadership abilities. “If a candidate is an E-6 and they made that in five years—that is actually very good and means they advanced quickly. All that information is lost in a conventional résumé; it isn’t conveyed,” he says.
Kamal Ahluwalia, Eightfold’s president, says veterans have many soft skills that aren’t picked up on a normal résumé, such as the ability to work in ambiguous environments. “They have this in spades, and they can work under pressure,” he says.
The problem with the government’s existing TAP program is that it is largely based on a self-assessment questionnaire about skills that the job seeker completes, combined with keyword searches for open positions, Hopkins says. But many veterans sell themselves short in terms of the skills they actually have, he says, and keyword searches can return an overwhelming number of potential jobs, with no good way to screen them to find the best opportunities. For instance, a combat engineer who did a search of the TAP’s job database for open engineering roles just in the Washington, D.C., area in October would have to weed through more than 22,000 possible roles.
By contrast, Eightfold’s software curates a list of specific job openings for a candidate. It also curates job candidates for employers. And, for servicemen and -women leaving the military, it curates a network of veterans in similar roles or closely related ones that job seekers can tap.
“For transitioning service members it is really important to have a relevant network—with an emphasis on quality and context,” Hopkins says. “In this case we are surfacing other veterans in the role that I’m a strong match for.”
Eightfold’s victory in the competition came with $720,000 in prize money and was also supported by the Defense and Veterans Affairs departments.
Law, the retiring master sergeant who helped Eightfold test its software, says having that connection with another veteran at prospective employers is often a decisive factor. “I think when I find that person in the company, there is a sense of comfort,” he says. “We as a military, we feel we are all a family whether we have known that person one day or several years. I do find that they have a better understanding of where you are coming from.”
Eightfold’s A.I. has been trained on more than a billion employee profiles that the company harvested from various public and proprietary data sets, which include public announcements of new hires in trade journals and posts from sources such as alumni magazines, along with information on how those people were promoted over time, Ahluwalia says. It used this data to teach its A.I. algorithm about more than 500,000 different job titles and what the 1.4 million underlying skills inherent in those jobs are. The algorithm then uses this information to try to forecast the likely career progression of any given job seeker.
The company has been backed by more than $180 million in venture capital funding since its founding, including a $125 million financing round announced last month that was led by venture capital firm General Catalyst, based in Cambridge, Mass., which valued the startup at $1 billion.