JANZZ.technology offers explainable AI (XAI)

Over the past decade, thanks to the availability of large datasets and more advanced computing power, machine learning (ML), especially deep learning systems, have experienced a significant improvement. However, the dramatic success of ML has forced us to tolerate the process of Artificial Intelligence (AI) applications. Due to their increasingly more autonomous systems, current machines are unable to inform their users about their actions.

Nowadays, most AI technologies are made by private companies that make sure to keep their data processing a secret. Furthermore, many companies employ complex neural networks in AI technologies that cannot provide an explanation on how they come up with certain results.

If this kind of system, for example, wrongly affects customers’ traveling, this might not be of great consequence. However, what if it falsely impacts autonomous vehicles, medical diagnoses, policy-making or someone’s job? In this case it would be hard to blindly agree with a system’s decision-making process.

At the beginning of this year, the Organization for Economic Cooperation and Development (OECD) put forward its principles on AI with the purpose of promoting innovation and trustworthiness. One of the five complementary value-based principles for the responsible stewardship of a trustworthy AI is that “there should be transparency and responsible disclosure around AI systems to ensure that people understand AI-based outcomes and can challenge them.” [1]

Explainable AI (XAI) has recently emerged in the field of ML as a means to address the issue of “black box” decisions in AI systems. As mentioned above, most of the current algorithms used for ML cannot be understood by humans in terms of how and why a decision is made. It is hence hard to diagnose these decisions for errors and biases. This is especially the case for most of the popular algorithms in deep learning neural network approaches. [2]

Consequently, numerous regulatory parties, including the OECD, have urged companies for more XAI. The General Data Protection Regulation, which took effect in Europe, provided the people in the European Union with a “right to a human review” of any algorithmic decision. In the United States, insurance laws force companies to elaborate on their decisions such as why they reject the coverage of a certain group of people or charge only a few with a higher premium. [3]

There are two main problems associated with XAI. Firstly, it is challenging to correctly define the concept of XAI. Furthermore, users should be aware of what the limitations of their knowledge are. If companies had no choice but to provide detailed explanations for everything, intellectual property as a unique selling proposition (USP) would disappear. [4]

The second problematic factor is assessing the trade-off between performance and explainability. Do we need to standardize certain tasks and regulate industries to force them to search for transparently integrated AI solutions? Even if that means putting a very high burden on the potential of those industries.

At JANZZ.technology, we try our best to explain to our users how we match candidates and positions. Our unique matching software excludes secondary parameters such as gender, age, or nationality and only compares skills, education/training, specializations, experiences, etc. It only uses aspects that truly matter in order to find the perfect candidates.

Instead of giving one matching score, our unique matching system breaks down all criteria such as functions, skills, languages and availability. This allows users to have a better understanding of the results and sets the foundation for reskilling and upskilling the workforce to be analyzed. Do you want to know more about the ways in which JANZZ.technology applies explainable AI solutions? Please write now to  sales@janzz.technology

 

 

[1] OECD. 2019. OECD Principles on AI. URL :https://www.oecd.org/going-digital/ai/principles/ [2019.9.17].

[2] Ron Schmelzer. 2019. Understanding Explainable AI. URL: https://www.forbes.com/sites/cognitiveworld/2019/07/23/understanding-explainable-ai/#6b4882fa7c9e[2019.9.17].

[3] Jeremy Kahn. 2018. Artificial Intelligence Has Some Explaining to Do. URL: https://www.bloomberg.com/news/articles/2018-12-12/artificial-intelligence-has-some-explaining-to-do[2019.9.17].

[4] Rudina Seseri. 2018. The problem with ‘explainable AI’. URL: https://techcrunch.com/2018/06/14/the-problem-with-explainable-ai/[2019.9.17].

 

 

 

 

In China’s industrial heartland city of Chongqing, a smart technology upgrading is on full display

The second Smart China Expo (SCE) was successfully held during 26-29 August in Chongqing China. Some of the most newsworthy Chinese business leaders, including Jack Ma Yun (Founder of Alibaba Group), Pony Ma Huateng (Chairman and CEO of Tencent), Robin Li Yanghong (Co-founder, Chairman and CEO of Baidu), Yang Yuanqing (Chairman and CEO of Lenovo Group), gathered in Chongqing  and shared their views on intelligent technology, offering their suggestions for the smart industry.

What is more, President of the People’s Republic of China, Xi Jinping, sent a congratulatory letter for the opening ceremony of the SCE and Chongqing was announced to be the permanent meeting place of this high standard event. But what makes this city the pioneer of the intelligent and smart industry in China? Perhaps the following aspects could give you some insights.

 China’s strategic development    

At the end of the 20th century and the beginning of the 21st century, the Central Committee of the Communist Party of China and the State Council carried out Deng Xiaoping’s thought of “two overall situations” in China’s modernization drive and made a strategy for the development of the western region. As the only municipality directly under the Central Government in Western China, Chongqing has ushered in historic opportunities and accelerated the pace of municipality development.

In 2013, the Chinese government took the “One Belt One Road” initiative as a global strategy, and Chongqing once again welcomed the golden opportunity for development. As the intersection of “Silk Road Economic Belt” and “Yangtze River Economic Belt”, the strategy of “One Belt One Road” accelerated Chongqing’s opening to the East and West.

After stepping on the express train to achieve high economic growth, Chongqing’s economy encounters downward pressure. In order to achieve a new round of growth, since 2018, Chongqing has implemented an innovation-driven development strategic action plan led by the intellectualization of big data.

Complete industrial chain   

Chongqing’s choice was clearly well thought out. Chongqing plays an important role in the integration of informatization and industrialization in China. It is one of the country’s oldest industrial bases in the West and an important industrial manufacturing base for the country. Additionally, the industry in Chongqing has got a relatively complete chain. Besides the traditional manufacturing industry, it also includes the electronic information and communication industry.

It is China’s largest manufacturer of cars and is home to some of the largest car manufacturers such as “Changan Ford” and “LIFAN”. It also produces one in every three laptops in the world. Having a good industrial foundation makes it feasible to transform and upgrade the industrial economy with smart technology.

 Well established digital platforms   

After several years of efforts, Chongqing has built a unified information sharing platform for the entire city. A three-level (country-city-district) government information resource sharing system links the national platform and 38 district platforms together.

Chongqing has taken the lead in completing data sharing at the provincial/municipality level, through which the isolated information islands of the departments can be bridged, and the data aggregation can be accelerated. More than 200 applications for government services, urban planning, urban governance, etc. within 80 departments have been realized.

Well established network infrastructure

Chongqing has become one of the 10 first-level nodes in the national communication network architecture, which have greatly enhanced Chongqing’s position as an internet hub in the West and the supporting capacity of Chongqing’s network infrastructure.

Chongqing has also become one of the two big cities in the Western Region where three operators (Mobile, Unicom and Telecom) have launched 5G pilot projects together. Thus far, Chongqing Mobile has opened two 5G base stations. Within this year, it plans to build and open 50 5G base stations in the main urban area.

 During the opening, the newest technologies, products and applications in the fields of artificial intelligence, big data, self-driving vehicles, drone and virtual technology, and so on, were presented and released. The exhibitors included several technology heavyweights such as Alibaba, Google, Inspure, Qualicomm, Huawei and Baidu.

Among the 843 companies from 28 countries and regions, JANZZ.technology was honored to take part in the SCE in Chongqing. We believe that China will be the leading country in smart technology in the future and we hope to seek potential Chinese partners that can help us open the door to the Chinese market. We could still recall the hundreds of youngsters we met during the expo. Through their excited eyes, we see the bright future of the city.

Where is the next generation of craftsmen in Switzerland? (And elsewhere?)

According to the latest Nahtstellenbarometers – Education Decisions after Compulsory Schooling, published by Innovation SBFI and State Secretariat for Education, Research and Innovation (SERI), the most desired professions for vocational training in Switzerland are commercial employees, followed by healthcare assistants and information technologists. This means that none of the professions in handicraft are among the top 5. Compared to boys, there are 15% less girls aspiring to follow the vocational training, and not one single girl reports to be interested in choosing an apprenticeship as electrician, as a car mechanic or as a polytechnical technician. [1]

There is currently a deficit of 42,778 handicraftsmen in Switzerland. This figure was published by a job search website that also pointed out that craftsmen jobs form one of the most advertised job category in years: currently, there is a total number of 198,097 vacancies advertised. Companies in construction, and building and dwelling services are struggling to hire skilled workers. Stefan Danev, Managing Director of an electrical and safety engineering company in Winterthur, ZH, says that “finding personnel to fill our vacancies in the long term is not easy under the current market situation”. [2]

 Growing interest in the academic route

What causes this shortage of craftsmen in Switzerland? The increasing popularity of the academic route is mentioned as a contributing factor for this development. Between the ages of 12 and 14, Swiss adolescents have to decide on going to pre-university baccalaureate schools or searching for apprenticeships offered by companies (this is known as the dual-track system).

Having a long tradition, the dual-track system was well received by parents, by adolescents and by society at large, as it has largely contributed to a very low youth unemployment rate and high levels of workers’ competency and of quality in all kinds of skilled trades in Switzerland.

However, a growing number of parents hold the perception that the vocational system has a lower quality and that students who enter vocational schools are less capable or have lower aspirations compared to students with four-year university degrees. This is especially the case among parents with migration background. International companies, too, add pressure by not recognizing graduates from vocational training as equal to graduates with a bachelor’s degree. This, in turn, forces a lot of young people to hesitate about pursuing vocational training.

Recently, there has been an increase in adolescents choosing the baccalaureate track, especially in the French and Italian parts of Switzerland. This poses a direct challenge for some of the professions in skilled trades. SERI noted in a statement that “across Switzerland, the baccalaureate has gained more interest and the desire for a general education is stronger than last year” [3].

Misconceptions in skilled trades

When looking at the media, one could think that the only prosperous professions in the future are computer-science-related, and that most skilled-trade jobs—especially handicraft—will be replaced by automation and robots. But under certain circumstances, machines do not yet have enough dexterity and fine motor skills to compete with human hands. For example, to grind bearings that has accuracy within a 100th of millimeter needs years of practice and only experienced skilled craftsman can do that and sometimes other than experience, it also required intuition which machines will never have.

One tends to have the misconception of skilled trades as providing little chance of climbing up the career ladder, and, hence, of offering a small salary. But the reality is that there are many top executives in big companies, as well as well-known government figures in Switzerland who have worked their way up from apprenticeship. Highly qualified craftsmen are particularly in demand today and their salary is likely to increase in the near future.

Moreover, the job provides the opportunity to become an entrepreneur. Unfortunately, there are many people in the skilled trades business who intend to pass on their very successful and lucrative business but cannot find a willing successor. Apart from the fact that few young people are trained in such business, it is also reported in various surveys that Generation Y/Millennials (born between 1980-1995) are seeking more security and flexibility in work and prefer having a good, stable salary in an international company, instead of taking on the responsibility of entrepreneurship.

Are young people getting too lazy?

In addition to Switzerland, many other countries like Germany, Belgium, Austria and the United States are facing similar shortages of craftsmen. It is an undeniable fact that the nature of many skilled trades jobs is hard, and that there is a general trend among parents who were in those professions to push their children towards more comfortable jobs. For example, in an apprenticeship at a bakery, one has to start the job at 2am, a tough job that many are unwilling to take up nowadays.

One hardly hears about a child saying that his/her dream job is to become a boilermaker, a metal worker or a welder, because few of them have the opportunity to get introduced to such professions at an early age. With no understanding of or even misconceptions about such jobs, more and more young people are likely to be discouraged from starting an apprenticeship in such professions.

Christoph Thomann, president of the Central Board of Vocational Education and Training Switzerland, believes that the skilled trades are outshined by an increased focus on computers and robots among young people [1]. However, digitalization should not only be regarded as a barrier from choosing vocational training. In fact, vocational training should embrace digitalization and promote an image of the digitalized craftsman, a modern and less traditionally masculine image that attracts more young people, even young girls, to the field.

A collaborative effort

As in the other economic sectors, digitalization has also made its way into skilled trades and is having a profound impact by increasing the productivity and reducing business costs. For example, by using data analysis, roofers can now measure a house with a 3D scanner to order the exact number of roof tiles needed.

Building information modeling (BIM) helps to realize the integration of building information, which ranges from the design, construction and operation of the building to the end of the whole life cycle of the project. A lot of different information is integrated into a three-dimensional model information database for the stakeholders. There are of course many more examples, including virtual reality, drones, 3D mapping and 3D printing.

Despite great efforts in raising awareness of the importance of the professions in skilled trades communities, reality is disappointing. Matthias Engel from the Swiss Building Association appeals to the federal government in Bern by saying: “It is important that politicians do not send the wrong signals. It is important that the government not only promotes secondary and university education, but also vocational training”.

Indeed, a greater effort to actively promote vocational training, diminishing the gap between young men and women and encouraging more young women to take apprenticeships in certain professions ought to be made by the government. Furthermore, it needs to be considered to bring in young people from other countries than Switzerland, if necessary.

What can AI and big data do for contractors, headhunting firms specializing in skilled trades jobs and government agencies planning to promote vocational training?  How can you use digital platforms to hire the people with the skills you need? Write now to sales@janzz.technology and let JANZZ.technology help you with our intelligent data.

 

[1] gfs.bern. 2019. Nahtstellenbarometer 2019. URL: https://cockpit.gfsbern.ch/de/cockpit/nahtstellenbarometer-2019/ [2019.07.25]

[2] Ulrich Rotzinger and Julia Fritsche. 2019. In der Schweiz fehlen 42’778 Handwerker. URL: https://www.blick.ch/news/wirtschaft/in-der-schweiz-fehlen-42778-handwerker-schreiner-sanitaere-und-elektroinstallateure-verzweifelt-gesucht-id15399544.html?fbclid=IwAR0TU2tUpeSmljN23gLwK5S09DOpvURnFdNqBNoR6nRSfLo_Z3ChojKrVYE [2019.07.25]

[3] Isobel Leybold-Johnson. 2019. What careers did Switzerland’s students choose this year? URL: https://www.swissinfo.ch/eng/continuing-education_what-careers-did-switzerland-s-students-choose-this-year-/45035674 [2019.07.25]

NRK shows success stories from Norway’s new job matching platform

JANZZ.technology is the provider of the technology behind the semantic search and matching engine of the Norwegian Labour and Welfare Administration’s (NAV) new job matching platform.

NAV’s digital job search platform, Arbeidsplassen.no, is now launched and endorsed by both job seekers and employers. NAV hopes it will now be easier for job seekers to find a new position.

Yusuf became a call center agent within a week. For him, taking a year off after high school also meant a gap in the CV, which turned out to be problematic when he was applying for a job again. Through NAV, he started work training, which would actively help open the door to the labor market. Arbeidsplassen.no was the solution for Yusuf. He got an interview and started as a call center agent the following week. For the recruitment company “Maskineriet”, NAV’s website has made it easier to find new employees. The recruiters search through NAV’s CV-database, find candidates and make further relations. The candidates may then be employed in a permanent position.

The managing director of Virke, the Enterprise Federation of Norway, praises the job search platform. Arbeidsplassen.no is seen as very important, as it connects companies’ needs and good candidates more efficiently. The fact that NAV is investing in digitization simplifies the recruitment process for companies.

On the job seeker side, the CV service has been significantly improved, thus candidates can more conveniently find the right job by using NAV’s platform. Candidates can now define and target the job search profile, and simultaneously apply to a wider range of available positions. The employers demonstrate positive feedback on both the candidate matching process and the platform Arbeidsplassen.no – which ultimately is important to NAV.

Learn more on NRK.no: https://tv.nrk.no/serie/distriktsnyheter-oestfold/201907/DKOS99070519/avspiller

 

 

Middle-skilled workers to be hit hardest by digitization

While low-skilled workers are going to suffer the most from the consequences of digital transformation long-term (with some exceptions), opportunities for middle-skilled jobs are shrinking the most, according to recent observations in OECD countries.

We used to talk about digitalization and automatization only as processes that will change our working environment in the future, for example through the replacement of humans by robots. Meanwhile, the situation has changed: many of us already feel the effects of digitization and automation. These effects are likely to be amplified even further in future.

Due to the energy revolution that digitalization induced, many companies in the energy business, blindsided by the speed of this revolution, are faced with overcapacity. In Switzerland, General Electric (GE) has just announced a major workforce reduction, which causes 450 employees in Baden and Birr to lose their job. In order to compete with international online providers Migros, one of Switzerland’s biggest retail companies, too, undergoes such transformation. In June, the Genossenschaft Migros Ostschweiz released the dismissal of 90 employees in Gossau. The Organization for Economic Cooperation and Development (OECD) predicts difficult times for Swiss employees: 700,000 jobs are associated with a “high risk of automation.” [1] Moreover, this is only a small, partial reflection of the whole, global labor market.

It is difficult to account for the full impact of digitalization since it bears both positive and negative effects for the job market. Statistical evidence however indicates that digitalization affects the distribution of work, income and wages. [2] With skills like problem-solving, creative thinking and complex communication that are complementary to digitization, high-skilled workers tend to benefit the most from digitalization. As a result, we can observe an increase in high-skilled jobs in most OECD countries. Likewise, the share of low-skilled jobs grew while the share of middle-skilled jobs decreased. [3]

Why are middle-skilled workers at greatest risk to be disadvantaged under digitalization? Martin Wörter, Professor of Innovation Economics at ETH Zurich explains that “repetitive activities in the office or in industrial production can be replaced more easily by computers or robots.” Federal employment statistics for Switzerland back up this statement. Within 20 years the number of office workers decreased by 150,000 while the number of craftsmen fell by 90,000. Conversely, the number of academic professions grew by 470,000. [1]

However, it is short-sighted for companies to simply lay off unqualified workers and to replace them with employees who fit the demanded skills profile. Since skill requirements are changing faster than ever, even if companies could replace their unqualified workers today, what about tomorrow? The only way to solve this problem is to enable reskilling of the existing workforce. Further training could largely reduce redundancies and benefit the company at large. As Bruno Staffelbach, Professor of Human Resource Management and President of the University of Lucerne, says: “Company-specific know-how will become even more important in the future. However, employees can only acquire these skills on the job in their company.” [1]

Many companies have realized this and adopted effective skills development programs.  However, as we have written before on this site, workforce reskilling requires an ecosystem approach that involves individuals, companies, industries, as well as governments. Based on calculations by the World Economic Forum, in the US 45% of workers at risk could be collectively reskilled through businesses working together. If combined with governmental efforts, this number could increase to even 77%. [4]

For almost a decade, JANZZ.technology has been watching and collaborating in many labor markets worldwide. We offer our know-how and the right data on skills and specializations to tackle general challenges in the job market. Our latest product, Labor Market Dashboard uses real time data in order to establish important labor market indexes such as the most required skills, the most searched for positions or the female/male ratio. Should we have caught your interest and should you wish to learn more about JANZZ.technology’s offers, please write now to sales@janzz.technology

 

 

[1] Albert Steck. 2019.Digitalisierung gefährdet Jobs von Mittelqualifizierten am stärksten. URL: https://nzzas.nzz.ch/wirtschaft/digitalisierung-gefaehrdet-jobs-von-mittelqualifizierten-am-staerksten-ld.1492570#swglogin [2019.07.02]

[2] OECD. 2015. OECD skills outlook 2015: youth, skills and employability, OECD Publishing, Paris, URL: https://doi.org/10.1787/9789264234178-en [2019.07.02]

[3] OECD. 2019. OECD skills outlook 2019: thriving in a digital world, OECD Publishing, Paris, URL: https://doi.org/10.1787/df80bc12-en [2019.07.02]

[4] Borge Brende. 2019. We need a reskilling revolution. Here’s how to make it happen. URL: https://www.weforum.org/agenda/2019/04/skills-jobs-investing-in-people-inclusive-growth/ [2019.07.02]

Occupational classification systems in the digital age

People have long been monitoring the economic activities of our society. It is said that during the Chinese Tang Dynasty (618-907) there were 36 different job types. Fittingly, the period marks the origin of the famous Chinese saying that ‘every trade has its master’ (san shi liu hang, hang hang chu zhuang yuan).

Today, jobs are changing at such a speed that it is almost impossible to give an exact number of the occupations that affect our daily life. Compiling statistical records of occupations is also becoming complicated since jobs are changing, disappearing and emerging. There used to be only ‘the’ manager, but now there is a PI manager, an IT manager, a project manager, an intergenerational engagement manager, you name it.

Thus, other than listing simply all occupations for statistical purposes, job descriptions, skill and experience requirements, education levels and more aspects are integrated, too, in occupation-related databases. That way, we can not only better understand the jobs of today but also develop more sophisticated systems that are able to perform more complex services with occupation data. For example, this enables performing the tasks of career planning, job searching, identifying trends or guiding policy design.

US-based classification systems

The United States Department of Commerce released the Standard Occupational Classification (SOC) in 1977. Back then, many programs by the US government began collecting statistics which is why the federal government needed a unified occupational classification system. SOC entails a short description and illustrative examples for each job. It is classified based on the type of work performed, but rarely on the level of skills and education needed for a specific position [1]. The latest version of SOC was published in 2018.

 The online database O*Net is an expansion of SOC and was created during the mid-1990s by the US Department of Labor’s Employment and Training Administration. O*Net can be freely accessed and downloaded by job seekers, students, businesses researchers and workforce development professionals alike. Compared to SOC, it is a much more sophisticated system with more detailed information such as tasks, technology skills, knowledge, abilities, education level and work style.

 Europe-based classification systems

The international Standard Classification of Occupations (ISCO) is maintained and managed by the International Labour Office (ILO). ISCO is the main international classification of occupation-related data and used for international exchange, reporting and comparison. It also serves countries and regions that want to either further develop their own occupational classifications or directly adapt one from ISCO-08. Examples include Ö-ISCO in Austria, Styrk-08 in Norway, COCR-2011 in Costa Rica, NOC 2016 in Canada and most national occupational classifications in Asia.

In July 2017, the European Union launched the first version of a European multilingual classification of skills, competencies, qualifications and occupations (ESCO) that is also based on ISCO-08. ESCO aims to create a common understanding of occupations, skills, knowledge and qualifications across the EU’s official 24 languages that enables employers, employees and educational institutions to better understand needs and requirements. Under freedom of movement ESCO could aid in making up for skill gaps and unemployment in the different member states, as the President of the European Commission Jean-Claude Juncker states [2].

Industry classifications

Industry classifications or industry taxonomies group companies by industry and in terms of production processes, products or job positions. They serve national and international statistical agencies for the analysis, comparison and summarization of economic conditions. Well-known industry taxonomies include NAICS, ISIC, GICS, NAF 2015 and MUPCS.

Furthermore, a shift from occupational classifications towards skills classification has been observed. This shift is linked to an attempt of improving classifications’ ability to aid in career guidance and the conduction of upskilling and reskilling. The United Kingdom and the innovation foundation Nesta have built the UK’s first data-driven skills taxonomy. It allows for measuring the country’s supply and demand of skills and for preventing skill shortages. The social media platform LinkedIn has also built a skills taxonomy for its users.

Chinese classification systems

China started to create its occupational classification in 1995. After four years, the country released its first version. Currently in use is a version from 2015 that aims to keep pace with the fast-changing employment sector. The Chinese classification has 4 digits with 1838 professions in total.

Compared to O*Net, which was created during about the same time period, there is still much room for improvement in the Chinese occupational classification. Specifically, it could be improved with regard to accessibility, continuous data updating and the provision of guidance for students and job seekers [3]. However, the problem of lacking in updated data is not unique to the Chinese occupational classification. This issue is shared with many other classifications, including O*Net.

A new concept for occupational classification systems

The creation of a traditional expert consultation taxonomy is time-consuming, costly and, most importantly, will lack the ability to continuously adapt to the world’s fast-changing working environment.  Therefore, a new solution is needed. One that can inform the labor market constantly and make job seekers, students, education providers, employers and policy-makers alert for change and empowered to react.

With digitalization, a data-based information collection methodology can revolutionize the way classification systems are created. At JANZZ.technology, we have mapped all international occupational classification systems and others in our ontology. (If you would like to learn about the difference between taxonomy and ontology, please check https://janzz.technology/ontology-and-taxonomy-stop-comparing-things-that-are-incomparable/).

This mapping allows us to analyze complex sets of occupational data and to annotate it with intelligent and standardized meta-data, which makes the data comparable in further processes like benchmarking, matching or statistical analyses. Our JANZZclassifier! is a product for everyone who has large volumes of (unstandardized) occupation-related data such as job titles, hard and soft skills and, particularly, training/qualifications. It enables you to simply run your data through our API and will return more meaningful data and, if desired, one of the standard classifications.

Above all, we are using real-time data, both from our users, our partners and the labor market in order to constantly update our database. It is the new way to develop classification systems in the digital age. Please write now to sales@janzz.technology if you wish to learn how our ontology may assist you.

[1] Jeffrey H. Greenhaus and Gerard A. Encyclopedia of career development.

[2] ESCO (2015). ESCO strategic framework. Vision, mission, position, added value and guiding principles. Brüssel.

[3] LI Wen – Dong and SHI Kan. 2006. A brief introduction to the development of the U.S. national standard occupational classification system and its implications to China. URL: https://www.docin.com/p-1479318301.html [2019.06.24]

Examples of NLP applications in talent acquisition

JANZZ’s ontology-JANZZon! fits the description of a natural-language processing application for talent acquisition and can be placed alongside Google’s Cloud Jobs API. Gartner’s article Impacts of Artificial Intelligence and Machine Learning on Human Capital Management summarizes that both AI and machine learning applications actively transform the ways in which HR processes are done today. To read the full report please go to: https://www.gartner.com/en/documents/3778864/impacts-of-artificial-intelligence-and-machine-learning-

Ambitious working women may find it hard in Switzerland

Despite being ranked among the world’s most livable places in terms of living standard, education, and healthcare, Switzerland’s cities might still not be the most ideal residence for aspirational working women, especially not for ambitious working moms. According to the 2018 Gender Gap Report, Switzerland ranked 20th. It specifically showed a significant gap between women and men in the areas of economy and political participation.

In Switzerland, women make up only 33.9 percent of senior positions, which include managers, senior officials and legislators. This share has barely changed over the past ten years. The report furthermore shows an inequality in income between women and men, with an estimated average income of $53,362 for women and one of $76,283 for men. [1] One might link the wide income gap to the disproportional representation of women in higher-ranking or higher-paid positions, occupations and industries, but the reasons are more complex.

Gender inequality, a global issue

Gender inequality in the workplace is a global issue that does not correlate directly with a country’s level of development. Thus, Switzerland is an illustrative example among many others. Extreme cases include Japan and South Korea. South Korea, one of the largest economies in Asia, recently made the abysmally low 116th place out of 144 countries in the World Economic Forum’s gender equality ranking [2].

As a part of one of the most advanced, wealthy and democratic nations, Japanese women have always been kept on the fringes of both the economic and political stage. In a worldwide comparison of developed countries, they thus remain in an extraordinarily disadvantaged position. Last year’s news about Tokyo Medical University illustrates this even further: the university altered the entrance examination scores of female candidates. Since such a move will only lead to even fewer female doctors in Japan, this makes the country’s society appear regrettably backward.

 Protest by women

For Swiss women, however, many things have developed positively since the advent of the #MeToo movement and the introduction of women’s quota. In tech and other sectors, personnel consultants observe a trend towards increasing the proportion of women in the executive committees. Simone Stebler from the personnel consultancy Egon Zehnder says that “today, gender diversity is an integral part of the business plan of most companies.” [3]

The Swiss multinational investment bank UBS wants to occupy at least one third of its leadership positions with women. The bank’s gender equality officer says: “We would like to see the proportion of women rising, especially in leadership positions.” Similarly, the pharmaceutical giant Novartis employs nearly as many women as men in its research cadre. Other international companies such as Swiss Re and Axa could also be counted towards such exemplary Swiss employers. [4]

Balancing the competing interests of family and work

However, global experts indicate that for women, the reconciliation of work and family still poses a big challenge. Difficulties in achieving a feasible work-life balance forced many women in Japan and South Korea to leave their jobs. In Switzerland, too, the traditional model of women as caretakers of the domestic realm persists, which is why part-time work is still the norm for Swiss working moms. According to the Federal Statistical Office, 4 out of 10 women work full-time, compared to 1.7 out of 10 men [3].

Valérie Borioli Sandoz, from the union group Travail.Suisse for equality policy, believes that part-time work is the “least bad solution for the reconciliation of work and family. However, it can be a trap, since it is very difficult to escape from it.” [5] Although part-time jobs are a luxury for Swiss moms, they also hold them back from taking certain occupations and higher positions in the workplace.

 One of the main reasons is cultural

Experts call on innovative and open ways to shape our working environment, including more flexible working hours and the co-fulfillment of top management roles. Even with structural changes in companies, the problem of missing female presentation will not be solved easily.

The traditional image of women counts as one of the major reasons why women participate less intensively in official labor markets. Gender and labor market expert Professor Barbara Riedmueller (Freie University in Berlin) points out that women occupying top positions are more accepted in countries where family services are traditionally outsourced. The primary examples are the Scandinavian countries. Gender equality can only be achieved if women no longer have to depend on men. This, however, is a question of changing the culture of a given society. [3]

 Valuing traditionally female occupations

Although there has been great progress for the rights of women in several societies, women are still often found in the working fields of health care, childcare and maintenance, where salaries remain medium to low. By contrast, men dominate high-paid fields such as computer programming, engineering, and technical work.  However, it is reductive to argue that women should only be encouraged to take more top management roles, to break into the male-dominated high-income industries or to demand equal payment in order to shorten the income gap.

 Currently, there are over 6000 professional care vacancies in Switzerland. This number has increased by double the size compared to five years ago.[6] While we need to promote gender diversity in less-female-dominated occupations and industries, we also have to improve women’s salaries, work-life balance, training and further education in traditionally ‘female careers’. This is necessary to reassert the value of such careers and to motivate more young people (male and female) to choose them as a profession. Eventually, this will benefit the health care sector and, as a result, society at large.

This can only be achieved if we all agree to increase the healthcare expenditure in order to heighten the wages in professional care. This way, governments have the financial resources to change the current situation. They need to financially support traditionally under-paid jobs, since caretakers and similar positions’ contribution to society is absolutely crucial. However, the question is whether everybody is really willing to pay for this.

For almost a decade, JANZZ.technology has been observing and working with many labor markets worldwide. We offer our know-how and the right data on skills and specializations to tackle general challenges in job market. If you are interested, please write now to sales@janzz.technology

 

 

[1] Swissinfo. 2018. Swiss gender partiy ranking shows slow progress. URL: https://www.swissinfo.ch/eng/global-gender-gap-report-_swiss-gender-parity-ranking-shows-slow-progress/44624274 [2019.06.13]

[2] Heather Barr. 2018. South Korean women are fed up with inequality. URL : https://www.hrw.org/news/2018/06/14/south-korean-women-are-fed-inequality [2019.06.13]

[3] Franziska Scheven. 2019. Berufstätige Frauen haben heute gute Aufstiegschancen – aber nur, wenn sie Vollzeit arbeiten. URL: https://www.nzz.ch/panorama/frauen-und-karriere-nach-metoo-kinder-hemmen-die-karriere-ld.1455524[2019.06.13]

[4] Franziska Phister. 2019. Mann oder Frau: wer schaff es nach oben? URL: https://nzzas.nzz.ch/wirtschaft/geschlechterkampf-mann-oder-frau-wer-schafft-es-nach-oben-ld.1458619#swglogin#swglogin [2019.06.13]

[5] Jessica Davis Plüss. 2019. Mothers face double-edged sword in Swiss workplace culture. URL: https://www.swissinfo.ch/eng/international-women-s-day_mothers-face-double-edged-sword-in-swiss-workplace-culture/44801716 [2019.06.13]

[6] Albert Steck. 2019. Offene Stellen auf Höchststand. http://jobs.nzz.ch/news/6/arbeitswelt/artikel/421/offene-stellen-auf-hochststand [2019.06.13]

What you should know when choosing your AI recruitment software

In a report, Deloitte presents the evolvement of HR technology in four stages. The first stage describes the period during the 1970s and 1980s, when the main attention of software vendors was on systems that help HR managers make records. During the second stage between the 1990s and early 2000s, capabilities to support recruiting, training and performance controlling were developed. Around 2010, at the third stage, vendors started to offer cloud services and more user-friendly systems to engage with employees’ self-services.

The Deloitte report claims that today we are in the fourth stage of HR technology. In order to react to work environment microtrends, vendors have to design tools that are targeted for teams, individuals and networks and also enhance people’s productivity. At JANZZ.technology, we too think that an HR software should assist HR managers in being more productive and in focusing more on value-added tasks. For example, it should reduce the effort needed for mundane tasks such as screening thousands of candidates and should enable to focus more on value-added tasks such as interviewing candidates. We further believe that this is going to be achieved by means of Artificial Intelligence (AI).

AI for recruiting

Talent acquisition is undeniably one of the most important parts of corporation management. This makes the recruitment software market the most competitive and interesting market to observe. Governmental organizations like Public Employment Services (PES) are also actively seeking solutions to deal with this matter. According to Crunchbase, solely in 2018 recruiting software startups received over $ 600 million of VC finance. In the latest Market Map by HR Tech China, recruiting software vendors constitute the largest part of all HR technology vendors.

The offers made by vendors include the testing and assessment of candidates, background checks, video interviewing and many recruitment platforms. Since early 2017, AI has emerged in the recruiting process. The ensuing rise of recruiting software’s so-called AI capabilities could make any HR manager feel overwhelmed.

‘AI for recruiting’ is an emerging technology used in HR recruitment processes. It employs AI technology and mainly aims to reduce repetitive, time-consuming and banal tasks, which helps recruiters and hiring managers focus on value-added activities. 52% of talent acquisition leaders state that the hardest part of recruitment is the screening of candidates from a large applicant pool. [1] For instance, an AI recruitment software can screen thousands of applications and recommend the top 5 candidates in a blink. Thus, HR managers using AI for recruiting will have more resources to assess the top picks in-depth, which in turn heightens their chance to really find the best suitable candidate.

By contrast, the larger public uses the word AI vaguely and often even inaccurately. Many companies use ‘AI’ to describe their products in order to make them appear as ‘upgraded to the next level’. In most cases, this sort of product advertising promises too much. It is therefore extremely important to be able to evaluate both such products and their vendors. The process is similar to that of hiring: only if you have various ways to assess options, you can find the best one possible.

Evaluating AI for recruiting technology

How should HR avoid over-promised software when choosing from all the products? We have come up with three principles to go by when choosing AI recruitment software:

Principle I: Be aware of the bias within AI recruiting software

Last year, the story about the Amazon AI recruiting tool secretly being biased against women was a wake-up call for all of us: machine learning can be just as biased as human beings. Therefore, it is extremely important to focus on algorithmic fairness and transparency.

You must be aware of how the software processes personal information data such as date of birth, gender and nationality. Which factors does the software take into consideration when matching? And does the software ignore irrelevant factors?

Apart from algorithms you have to make sure that the software has representative training data. In the case of the Amazon AI recruiting tool, the tool turned against female applicants because, for over ten years, the company trained its computer models with resumes summited by male applicants. Hence, make sure you ask your software vendor how they deal with their data source.

Principle II: Be sure to test before you purchase

Before buying a car, you would certainly test drive it first. This rule applies to buying recruiting software as well. Since a recruitment software system is an expensive and long-term investment for your business, it is wise to complete a POC (proof of concept).  In this trial run you’ll find out if the software can really solve your prioritized problems, perform the promised functions and handle your data within the required scale and scope.

JANZZ.technology conducted a POC with an intergovernmental organization to find out if our solution can truly help them save time when finding suitable candidates. Our AI software competed against their HR team in matching candidates worldwide to their open junior intern positions. After screening over thousands of applications, they were pleasantly surprised by our results.

Most good software vendors offer free trials. It is important to prepare your test data well in order to get the most out of your practice and maximally optimize this process. One of the often-ignored aspects when choosing a recruitment software is the maintenance and support needed after the purchase. Only with constant updating, the software is able to develop in parallel with the fast-changing markets, customer requirements and ongoing digitalization. Don’t simply trust marketing lines such as “50 other leading companies from your industry are use our software” or “top 100 out of the top 500 companies are also using our software”.

Principle III: Taking the “soft skills” of an AI recruiting software into consideration

Just like assessing a job candidate by evaluating his/her skills and soft skills, an AI recruiting software has its skills and soft skills as well. We determine the hard skills of a software as functionality, accuracy, data security, speed, languages capability and similar highly valuated competences.

However, many might overlook the soft skills of an AI recruiting software. Soft skills of an AI recruiting software are the ability to deeply understand the language, education, working and social system etc. of your practice region, and the ability to localize certain regions or countries.

For instance, a country like Spain has more than one language: Castilian(Spanish), Catalan, Valenciana, Galician and Basque. A good AI recruiting software should be able to understand the different languages and know the common terms that are used in the four different languages to refer to exactly the same thing.

Conducting job matching across Europe is not an easy task, for instance because each of the 44 countries has its own education system (even with the bologna framework). It is an enormous amount of work to compare the different education levels and match people to jobs. Does your vendor have the right knowledge to solve such problems within your practice region?

Besides language and education, there are many more and equally important categories that need to be taken seriously.  As an international corporation operating in different countries, you want to have a software which understands all your markets.

Limitations of AI 

You may have heard of all the promised benefits of using an AI recruiting software. Before the AI can do its magic, we are here to give you a word of caution. Don’t expect the AI software to make the hiring decision on its own. Many of the previous use cases proved to us that the technology just is not ready yet. “How to make sure the algorithm is really interpretable and explainable – that is quite far off.” [2]

If you are expecting AI and the algorithm to do their job well, it is equally important for you to check your company’s or organization’s readiness for AI, in order to maximize its power. We all know that identifying patterns and making predictions requires a large quantity of data. With the widespread open-source algorithms, the real game changer is the data used to train the algorithms. Any business or organization should have a clear plan on how to generate the quantitative and qualitative data which will help your AI recruiting software get more accurate results, this is economically profitable for your business as well.

JANZZ.technology supplies AI solutions for your recruiting system and helps you find the right skills and talents. The ontology JANZZon! and the smart matching engine JANZZsme! make complex problems such as job and skills matching computable and completely change the way we handle skills and talent searching. The applications of JANZZ.technology are structured semantically, meaning occupations, specialization, function, skills and qualifications etc. are interlinked logically. The JANZZ.technology applications can deliver meaningful results for complex searches in real time and across multiple languages. Our applications are constantly fed with new data generated from our users, therefore they become more accurate over time. Let the tools of JANZZ.technology assist you in finding your best fit candidates.  For a demo, please write now to sales@janzz.technology

[1] ideal. 2019. AI for recruiting: A definitive guide for HR professionals. URL: https://ideal.com/ai-recruiting/ [2019.05.28]

[2] Jeffrey Dastin. 2018. Amazon scraps secret AI recruiting tool that showed bias against women. URL: https://www.reuters.com/article/us-amazon-com-jobs-automation-insight/amazon-scraps-secret-ai-recruiting-tool-that-showed-bias-against-women-idUSKCN1MK08G [2019.05.28]

How India leverages its demographic dividend

While most of the developed countries in the world are fighting against their aging populations by increasing the retirement age and welcoming migrants, other countries are worrying about how to fit large numbers of young people into the workplace. Deloitte’s Voice of Asia series reported that many countries in Asia have witnessed steady growth in their working age population, with more and more young men and women entering the labor markets each year. India is the top one country on the list.

According to the numbers from the World Economic Forum, half of India’s population is below the age of 25 and a quarter is below the age of 14. Bearing in mind that it is the second most populated country in the world, with 1.3 billion citizens, India makes up for a fifth of the world’s youth. As most economists predicted, India will benefit from the demographic dividend and will have a fast-growing economy.

To realize the demographic advantage, India will need to majorly accelerate job creation and investment in human capital to keep up with the growing working-age population. For currently, there are 17 million yearly entrants into the job market and only 5.5 million created jobs. [1] In a survey conducted by the OECD, over 30% of India’s youth aged from 15 to 29 are neither employed nor in education or training (NEETs). [2]

Isabelle Joumard, senior economist and head of the India desk at the OECD explained: “NEETs include all youth left outside paid employment and formal education and training systems. They are NEET because there are not enough quality jobs being created in the system and because they have little incentives or face too high constraints to be in the education and training systems.” [2]

Looking from a global point of view, youth unemployment rates remain above 20% in some European economies, the Middle East and North Africa have had youth unemployment rates close to 30% and things have continued to worsen over recent years. Nevertheless, the young people who have found work often have to content themselves with jobs that fail to meet their expectations [3] and 16.7% of working youth in emerging and developing economies live in extreme poverty [4].

Why are employment opportunities especially scarce in the least developed countries? Insufficient policy development, poor infrastructure and limited financing channels are among the many reasons for job shortages. According to the findings of e4e (an education for employment initiative driven by the International Finance Corporation and the Islamic Development Bank), the mismatch between education and the labor market demand is a major obstacle to job creation. [5]

As pointed out by several reports, developing an employability-driven skill ecosystem is key for leveraging India’s demographic potential. Rajasthan, the seventh most populated state in India, has a youth population aged below 25 that makes up nearly 55% of the state’s entire population. From 2012 to 2018, its unemployment rate increased from 4.5% to 7.7%. The problem of unemployment in Rajasthan is compounded with issues, such as the lack of quality trainers and the non-alignment of education and skilling. [6]

To tackle these problems, the state has continuously intensified the establishment of education infrastructure. In 2004 it became the first state in the country to implement a skill mission aiming to reduce the gap between demand and supply of skilled workforce and hence increase the employment rate. To further improve the quality of skilling, Rajasthan has founded skill universities, a pioneer project in the country. [6]

In Himachal Pradesh, located in northern India, a large share of employment is in agriculture. More than two thirds of its manpower are self-employed, and the amount of salaried jobs remains very low. In 2018, the Asian Development Bank (ADB) signed a loan with the Indian government to leverage the technical and vocational education and training (TVET) institutions and to scale up skilling ecosystems in Himachal Pradesh.  The plans for the project include transforming 11 employment exchanges into model career centers, modernizing training equipment, employing a training information system and creating better access to quality market-relevant TVET for the state’s youth, in order to prepare them for the changing needs of the labor market. [7]

JANZZ.technology helps governments place workforce into labor markets with AI technology. In collaboration with MTESS and DGE, we have successfully implemented ParaEmpleo — a job matching solution in Paraguay. The collaboration between Paraguay and JANZZ.technology is within the framework of the Support Program for Labor Insertion which was supported by the Inter-American Development Bank (IDB) since 2011.  The representative of IDB in Paraguay, María Florencia Attademo-Hirt, spoke highly of JANZZ’s technology, saying: “Innovative tools like this are what will improve the lives of Paraguayans, beyond the Mercosur and regional context”. [8] The innovative use of technology is the right way to solve today’s labor market problems. If you as a governmental organization are looking for solutions to fight against labor market issues in your country, please write now to sales@janzz.technology

 

 

[1] NASSCOM, FICCI and EY. 2017. Future of jobs in India – A 2022 perspective. URL: https://www.ey.com/Publication/vwLUAssets/ey-future-of-jobs-in-india/%24FILE/ey-future-of-jobs-in-india.pdf [2019.04.30]

[2] OECD. 2017. OECD Economic Surveys India. URL: https://www.oecd.org/eco/surveys/INDIA-2017-OECD-economic-survey-overview.pdf [2019.04.30]

[3] Guy Ryder. 2016. 3 ways we can tackle youth employment. URL: https://www.weforum.org/agenda/2016/01/3-ways-we-can-tackle-youth-employment/ [2019.04.30]

[4] ILO. 2017. Global employment trends for youth 2007. URL: https://www.ilo.org/wcmsp5/groups/public/—dgreports/—dcomm/—publ/documents/publication/wcms_598675.pdf [2019.04.30]

[5] Lars Thunell. 2012. How do we create more jobs for young people? URL: https://www.weforum.org/agenda/2012/01/how-do-we-create-more-jobs-for-the-youth/ [2019.04.30]

[6] Pwc and FICCI. 2019. Fast forward: relevant skills for a buoyant Indian economy. URL: http://ficci.in/spdocument/23062/FICCI-PwC-rajasthan-report.pdf [2019.04.30]

[7] ADB. 2018. ADB, India sign $80 million loan to help boost youth employability in Himachal. URL: https://www.adb.org/news/adb-india-sign-80-million-loan-help-boost-youth-employability-himachal [2019.04.30]

[8] IDB. 2019. Algorithms that get you a job in Paraguay. URL: https://www.iadb.org/en/improvinglives/algorithms-get-you-job-paraguay [2019.04.30]