Digital economy

Digital Economy and Social Security Observatory

The Digital Economy will profoundly transform our daily life, how we work and how we live.

The Observatory will provide ISSA members with an understanding of the opportunities and the challenges it will present to social security administrations.

It will look at this transformation from two angles: the changing environment in which social security institutions evolve and how Social Security institutions themselves will be impacted and can respond to these challenges.

 

Large scale automation

Large-scale automation of industrial production and services is based on applying a range of advanced technologies such as Artificial Intelligence, cognitive computing, big data, Blockchain, Internet of Things and robotics among others.

Although very diverse, the application of these technologies enables the automation - to varying extents – of a number of tasks usually done by people. Some examples are the usage of increasingly autonomous robots in industrial production lines, self-services managed by artificial intelligence systems, and autonomous vehicles. These all combine all the technologies mentioned.

While such large-scale automation will undoubtedly impact on employment, the implementation of such automated systems is highly complex and potentially costly Furthermore, these “intelligent” systems have to be “trained” to specific application scenarios - which adds complexity and costs. Their potential usage cannot cover a large spectrum of activities such as creative and analytical ones (e.g. determining if software systems are correct).

Social security administrations could anticipate local impacts, particularly unemployment scenarios, and promote reconversion through training. Also, the construction, installation and training of these systems constitute economic activities themselves which require business know-how.

Ten global challenges for social security

Media Monitor Media Monitor

31 July 2017

forrester.com (03.04.2017) Forrester released an update to its Future Of Jobs research, which predicts how robots, automation, and artificial intelligence (AI) will impact the workforce over the next 10 years. While automation and related technologies will inevitably displace some of the workforce, Forrester argues that the technology will transform the workforce by adding new jobs or changing existing jobs, rather than completely displacing workers.

27 July 2017

Global Credit Research (17.05.2017)  The accelerating adoption of robotics in manufacturing in some of the worlds' more advanced economies could pose challenges to emerging market exporters that have benefited from their comparative advantage of lower cost, high skilled labor, says Moody's Investors Service in a report.

26 July 2017

El Cronista (25.07.2017) La automatización y robotización ponen en jaque al 52% de los empleos en México, dice el Instituto Global McKinsey. Son 25,5 millones de puestos de trabajo los que están en riesgo por la llamada cuarta Revolución Industrial.

26 July 2017

McKinsey Global Institute (30.06.2017) Companies new to the space can learn a great deal from early adopters who have invested billions into AI and are now beginning to reap a range of benefits. After decades of extravagant promises and frustrating disappointments, artificial intelligence (AI) is finally starting to deliver real-life benefits to early-adopting companies. Retailers on the digital frontier rely on AI-powered robots to run their warehouses—and even to automatically order stock when inventory runs low. Utilities use AI to forecast electricity demand. Automakers harness the technology in self-driving cars.

26 July 2017

McKinsey Quarterly (25.07.2016) The technical potential for automation differs dramatically across sectors and activities. As automation technologies such as machine learning and robotics play an increasingly great role in everyday life, their potential effect on the workplace has, unsurprisingly, become a major focus of research and public concern. The discussion tends toward a Manichean guessing game: which jobs will or won’t be replaced by machines?

21 July 2017

Les Echos (06.06.2017) Le développement des nouvelles technologies, des outils communicants, les impératifs croissants de réactivité, l'aspiration des salariés à une meilleure articulation entre vie pro et perso, conduit les entreprises à repenser leur organisation physique. Un changement de fond, dont elles ont tout intérêt à tirer profit.

14 July 2017

Eurofound (13.07.2017) This report examines developments in non-standard employment over the last decade. It looks at trends in the main categories of non-standard employment – temporary, temporary agency and part-time work and self-employment – based mainly on data from the European Union Labour Force Survey. The report includes a specific focus on work mediated by digital platforms, which is the most innovative of the new forms of employment that have emerged in the past decade.

14 July 2017

Zilient - Reuteur (21.07.2017) Thousands of Syrian refugees in Jordan's Azraq camp don't pay for their food with cash but by a scan of their eyes. Purchases are then recorded on a computing platform based on blockchain - the technology behind bitcoin. The U.N. agency launched the futuristic system in May as a one-month pilot involving 10,000 of Azraq's more than 50,000 inhabitants in a bid to explore blockchain's potential to cut costs and bottlenecks.

13 July 2017

lemonde.fr (11.07.2017) Un rapport commandé par Theresa May préconise de lutter contre les abus de l’« économie des petits boulots ». Mais les premières réactions des syndicats ne sont pas tendres.

12 July 2017

Financial Times (11.07. 2017) Government should encourage companies to improve employment options. Some view the gig economy as a flexible working arrangement, while others see it, if not straightforwardly as a form of exploitation, then as one that allows for very little employment protection. But if companies like Deliveroo or Uber were mandated to offer their workers a choice of employment options, wouldn’t this help ensure workers were being treated fairly?

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31