Social impacts of the platform economy

Platforms create value well beyond economic profits, and the topic of social and societal impacts resulting from the emerging platform economy has been getting more and more attention lately. Platform economy undoubtedly has both positive and negative impacts on individuals and families as well as wider communities and entire societies. However, the range and depth of these impacts can only be speculated, as only very early evidence and research on the topic has been produced. After all, the platform economy is only in its infancy.

Why is this important?

Platforms have potential to address major societal challenges such as those connected to health, transport, demographics, resource efficiency and security. They could massively improve our individual daily lives as well as contribute to equal opportunities and progress in developing economies. On the other hand, platform economy can result in negative impacts in the form of disruptions and new threats. Privacy and safety concerns have deservedly been acknowledged, and other possible risks include those related to social exclusion, discrimination and the ability of policies and regulations to manage with whatever platform economy may bring about.

Some examples of positive and negative social impact categories of the platform economy include the following, which may distribute equally, create further division or bridge the gap among various social segments:

  • employment and unemployment
  • livelihood and wealth
  • education and training
  • skills, knowledge and competences
  • health and physical wellbeing
  • mental health and wellbeing
  • privacy, safety and security
  • social inclusion or exclusion, access to services, etc.
  • new social ties and networks, social mixing
  • social interaction and communication: families, communities, etc.
  • behaviour and daily routines
  • living, accommodation and habitat
  • personal identity and empowerment
  • equality, equity and equal opportunities or discrimination
  • citizen participation, democracy
  • sufficiency or lack of political and regulatory frameworks.

Platforms may have very different impacts on different social groups, for example, based on age, gender, religion, ethnicity and nationality. Socioeconomic status, i.e. income, education and occupation, may also play an important role in determining what the impacts are, although it is also possible that platform economy balances out the significance of suchlike factors. One important aspect requiring special attention is how to make sure that vulnerable groups, such as the elderly or those with disabilities or suffering from poverty, can be included to benefit from the platform economy.

Things to keep an eye on

Value captured and created by platforms is at the core of our Platform Value Now (PVN) project, and there are several other on-going research strands addressing social and societal impacts of the platform economy. One key topic will be to analyse and assess impacts of the already established platform companies and initiatives, which necessitates opening the data for research purposes. To better understand the impacts and how they may develop as platform economy matures is of upmost importance to support positive progress and to enable steering, governance and regulatory measures to prevent and mitigate negative impacts.

Selected articles and websites

Koen Frenken, Juliet Schor, Putting the sharing economy into perspective, Environmental Innovation and Societal Transitions, (2017)
The Rise of the Platform Economy
Uber and the economic impact of sharing economy platforms
VTT Blog: Openness is the key to the platform economy
SUSY project: Solidarity economy

Heidi Auvinen

Research Scientist VTT Technical Research Center of Finland Ltd
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Alternative forms of platforms in ridesharing

Services like Uber and Lyft are the dominant platforms when it comes to getting a ride from A to B. Recently there has been a movement to delete the Uber app, driven the companies actions in relation to president Trump’s so called Muslim ban. This has benefited Lyft, but also drawn attention to other alternatives. These alternatives use platform thinking not only to optimize the matching of drivers and customers, but also to restructure the way value is shared.

Why is this important?

Different forms of platforms lead to different impacts. Lyft and Uber operate as companies seeking growth and maximizing value for their shareholders. This leads them to focus on scaling and increasing efficiency. On the other hand, locally based platform cooperatives, such as Denver-based Green Taxi Cooperative, try to grow to a sustainable size and share the profits among workers and users of the platform. Green Taxi Cooperative was born as a reaction to Uber by the local taxi industry and could be seen as an example of a counter trend to global winner-takes-all platforms.

La’Zooz, on the other hand, utilizes the decentralization enabled by blockchain and is an example of a distributed, decentralized organization owned by its users. Libre Taxi is an open-source app freely implementable by anyone. What is noteworthy in these decentralized alternatives is that they can cater for situations where companies like Uber have no interest, such as ridesharing in Siberia.

Things to keep an eye on

The #DeleteUber issue is an interesting example of the direct power of consumers in platforms. The question that remains to be seen is whether these kinds of movements have any actual impact, or does the ease of use make users forget about the behaviour of the platform company. The emergence of platform cooperatives and the adoption of blockchain-based services will undoubtedly change the forms of platforms. Also it is interesting how complex services can already be built on top of other platforms (Libre Taxi is built on top of messaging service Telegram).

Selected articles and websites

#DeleteUber reportedly led 200,000 people to delete their accounts
Denver Taxi Drivers Are Turning Uber’s Disruption on Its Head
Green Taxi Cooperative: Building an alternative to the corporate “Sharing Economy”
La’Zooz: The Decentralized, Crypto-Alternative to Uber
La’Zooz website
LibreTaxi website
Uber-like app in no time with JavaScript and secret sauce

Mikko Dufva

Research Scientist VTT Technical Research Centre of Finland Ltd
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Agriculture in the platform economy

The opportunities with platforms do not limit to specific high-tech industries only, but spread across the society and the economy. One sector that has so far received little attention, yet holds great economic, societal and environmental promise, is agriculture.

Why is this important?

Applying digital technologies to agriculture could improve the quality, efficiency and safety of farming and the down-stream industries such as food, textiles and fuels. Although digitalisation within agriculture has been modest compared to some other sectors, platforms have been or are being developed to for example the following use contexts:

  • farm management information systems
  • machine and equipment management; including asset-sharing
  • irrigation, fertilization and pesticides; including monitoring and optimisation
  • use of automation and robotics
  • food processing
  • management of subsidies.

In the centre of it all is the farm and the farmer, and platforms could, besides boosting performance of the farm as a unit, facilitate interaction between producers and other businesses along value chains and value networks. Platforms could even involve the end-customers as well as the public sector, in their roles as consumers and authorities.

The opportunities of platform economy paint a more sustainable picture of agriculture, enabling better economic performance as well as less environmental burden. Animal health and welfare could be improved and aspects of safety and ethics of end-products could be better addressed and traced. Imagine being able, as a consumer, to make affordable and fully informed choices on food and clothes, matching your personal values!

Things to keep an eye on

Currently most platforms in the agriculture sector are fragmented to small, unique solutions with little or no connectivity or interoperability to other systems. However, the vast potential of more integrated and interactive solutions to connect entire value networks are envisioned, and strategic efforts are on-going for example on the European level. The Digitising European Industry initiative has carried out extensive work, including exploration of platforms for industry, and Smart Agriculture has been identified as one vertical perspective of specific importance.

Empowering the farmers is a prerequisite for boosting digital technologies and platform economy development in agriculture. Technology developers need to establish an alliance with farmers to pinpoint concrete opportunities and co-innovate.

Selected articles and websites

Working Group 2: Strengthening Leadership in Digital Technologies and in Digital Industrial Platforms across Value Chains in all Sectors of the Economy, First report (December 2016)
Digitising European Industry initiative
EIP-AGRI: Agriculture & Innovation
GODAN, Global Open Data for Agriculture and Nutrition
365FarmNet: Agricultural management software
SMAG, Smart Agriculture: Farming information systems, cloud computing & SaaS, mobile applications

Heidi Auvinen

Research Scientist VTT Technical Research Center of Finland Ltd
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Technophobia – fear of technology

Although new technology intrigues us and makes us curious about what can be achieved with it, the flipside of the human reaction to anything new is suspicion and even fear. Technophobia means fear of technology, and it can stem, for example, from not fully understanding how something works, possibility of danger and negative impacts or risk of malicious misuse. Another flavour of technophobia is anxiety over our personal competences to deal with new technologies and the downright possibility of social exclusion if we lack the access or skills to adopt them.

Why is this important?

Some of the technology fears connected to the platform economy have been around for a long time, and they apply to pretty much any technologies linked to machines and computing. The archetype of suchlike concerns is the fear of losing our jobs because of automation, something that has been a worry for well over a century.

Another major concern in the context of platform economy is how the disruption to economy will impact us as individuals (for example moving from regulated labour market to the gig economy), as businesses (for example smaller companies being bulldozed by large platform corporations) or as society (for example governments trying to keep up with regulation, legislation and fiscal needs related to platforms).

Fears do not either escape the indirect risks and negative impacts that may arise with platformisation, such as loss of knowledge and survival mechanisms if digitalised assets are destroyed or if there’s a prolonged power cut. Intentional misuse and criminal activity is also a scare experienced by many, and evolving platform configurations may indeed be extremely vulnerable.

Examples of specific fears include:

  • Fear of technology eliminating jobs and the need for human workers.
  • Fear of technology taking over the human (individual or society).
  • Fears related to privacy and cyber security.
  • Fear of losing control and getting lost in the technology mesh.
  • Fear of not learning the skills or not having access to use a technology.
  • Fear of dependence and not surviving without the technology (for example in case of a power cut).
  • Fear of negative social and societal impacts (for example lack of face-to-face interaction).
  • Fears related to fast and vast information flows (for example validity of news).
  • Fear of governments not having the means to monitor and control malicious and criminal activity related to new technologies.

Things to keep an eye on

The important thing is to try understand the root causes of fear of technology in the context of platform economy, regardless of whether the threats are real or perceived. Also, it should we noted that technophobia may influence not only consumers but businesses and policy-makers alike. Through addressing technology-related concerns appropriately we can ensure that individuals as well as companies and other organisations have the courage to make the best of the platform economy opportunities. On the other hand, the assessment of fears helps us to pinpoint risks and vulnerabilities that need to be fixed in technological, regulatory or other terms. To dispel mistrust, impartial and validated information to support technology proficiency and awareness is needed. Similarly important are also investments in for example digital security and technology impact assessment.

Selected articles and websites

Robots have been about to take all the jobs for more than 200 years. Is it really different this time?
The Victorians had the same concerns about technology as we do
Fear of Technology
Hot Technology Pilots in 2016 – Fear & Chaos in Technology Adoption
Why do we both fear and love new technology?
Americans Are More Afraid of Robots Than Death. Technophobia, quantified
Ever-present threats from information technology: the Cyber-Paranoia and Fear Scale
The access – Platform economy: Creating a network of value
Choosing a Future in the Platform Economy: The Implications and Consequences of Digital Platforms

Heidi Auvinen

Research Scientist VTT Technical Research Center of Finland Ltd
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Digital Twins (of products)

The concept of a ‘digital twin’ has been suggested as one of the top technology trends for 2017, but what is it all about? The digital twin is the virtual counterpart of a real physical product, and it captures the data and information related to a product’s lifecycle from design and manufacturing all the way to use and final disposal.

Why is this important?

The existing applications of digital twins include for example storing and accessing product information using RFID codes and computer-aided 3D design models. However, technology development under the megatrend of digitalisation holds promise for way more radical progress with digital twins: In-house manufacturing applications are about to step up towards solutions across entire supply chains and end-use. The lacking connection and integration between the virtual model and the physical product will be intensified towards dynamic use of data and information flow. And the advances in blockchain technologies, artificial intelligence (AI) and autonomous systems will level up the importance of digital twins, as decision-making, transactions and learning will growingly rely on interconnected products and systems, i.e. Industry 4.0 and the internet of things (IoT).

Things to keep an eye on

The role of the digital twin in the platform economy is central, as it can ideally be the universal access point for all product information as well as accumulated data along a product’s lifecycle. For design, modelling and manufacturing of products the use of digital twins is typically managed with dynamic software models. These will be in the near-future even more closely interconnected to production processes and equipment, and applications are expected to spread and evolve from manufacturing industries to many other contexts such as end-user interfaces, transport sector, service industries, etc. Platforms managing and making use of all these data, information and interconnections will evolve, and the business models to product and service industries are going to change too. Visionaries anticipate even more radical opportunities in the longer term as digital twins of products and services will be followed by digital representations of facilities, environments, people, businesses and processes.

The digital twin is much more an opportunity than a threat, as the involvement of the virtual dimension aims to improve the quality, efficiency and performance of products, services and processes rather than replacing or displacing the real physical counterpart. In fact, the digital twin has been claimed to support the human knowledge kit, boosting problem solving and innovation by enhancing our uniquely human capacity to conceptualise, compare and collaborate.

Selected articles and websites

Gartner’s Top 10 Strategic Technology Trends for 2017
How To Put Your Digital Twin On Steroids
Leveraging Digital Twins To Breathe New Life Into Your Products And Services
Digital Twin: Manufacturing Excellence through Virtual Factory Replication
About The Importance of Autonomy and Digital Twins for the Future of Manufacturing
Digital Twin Data Modeling with AutomationML and a Communication Methodology for Data Exchange
Digitalization in machine building: The digital twin
GE Digital Twin Game

Heidi Auvinen

Research Scientist VTT Technical Research Center of Finland Ltd
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Chatbots and conversational commerce

Why is this important?

Chat and messaging has become a natural part of our everyday interactions with one another. It is still dominantly between humans, although the rise of conversational commerce has been predicted for some years. Conversational commerce means using chat or natural dialogue interfaces for interacting with a company, much like would be done with a sales clerk. The conversation can be between consumer and business, consumer and shopping assistant or merchant and back-office system. Using chat or messaging is a natural interface which works well for mobile, scales well into new features, supports multiple devices and is familiar to most. Therefore it is very lucrative for businesses.

Things to keep an eye on

Conversational commerce advances in two frontiers: in platform specific chatbots and integrated into other messaging apps such as WeChat or Messenger. The advances in artificial intelligence have enabled more fluent conversations to take place with chatbots, making them more usable. There is also increasing amount of commercial offerings integrated into messaging apps. It is also worth looking how voice activated personal assistants such as Siri or Alexa evolve in terms of recommending where to shop.

Selected articles and websites

The conversational commerce hype is real
Watch Out for the “Conversational Interface” in 2017
Chatbots and VR lead this season’s top tech trends in retail
The inevitable march of the chatbots into conversational commerce
2016 will be the year of conversational commerce
Start building Actions on Google

Mikko Dufva

Research Scientist VTT Technical Research Centre of Finland Ltd
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Use cases of AI for platforms

Why is this important?

There is currently a lot of hype around artificial intelligence (AI), but what opportunities does it offer for platforms? Roughly put: intelligent interfaces, comprehensive collection and advanced analysis of data. Chatbots and other conversational interfaces offer a natural way for people to communicate with a service offered by the platform, either via typing or voice. AI can offer customer service, online tutoring, expert advice or even a personal assistant. In the background it can go through massive amounts of data and recognise patterns. This has applications from health diagnosis to extracting information from street signs and from combating fraud to identifying key “influencers” of social media. The more data is fed to AI, more capable it gets.

Things to keep an eye on

All the big players are investing heavily in AI, with the hopes that they become the de facto platform for all things AI. How this plays out remains to be seen. It is also uncertain how the public opinion towards AI evolves: so far we have been a bit wary of letting always on personal assistants into our living rooms or trusting AI with our health data. The ethics of AI are still being discussed although the technology and services are advancing rapidly.

Selected articles and websites

Artificial intelligence and the evolution of the fractal economy
How Artificial Intelligence and Robots Will Radically Transform the Economy
7 Ways to Introduce AI into Your Organization
Google, Facebook, and Microsoft Are Remaking Themselves Around AI
Here’s What Artificial Intelligence Will Look Like in 2030
Why artificial intelligence is the future of growth
Would you want to talk to a machine?
Google’s Featured Snippets on Desktop Now Written By Artificial Intelligence
Uber Bets on Artificial Intelligence With Acquisition and New Lab

Mikko Dufva

Research Scientist VTT Technical Research Centre of Finland Ltd
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Hyperledger and open blockchain

Why is this important?

Blockchain can be used for many services in platforms, such as for distributed and secure digital rights management or payments, ensuring identity or making smart, self-actualising contracts. While it is currently being used mainly for digital currencies such as bitcoin, it is increasingly being used in other areas. In order to enable more wide and open use and seamless cross-industry interaction between different blockchain-based services, Linux foundation launched an open-source project called Hyperledger. The goal is to create a common infrastructure and standard regarding membership management, blockchain technology implementation, transactions and the blockchain code for writing e.g. smart contracts. The project is already backed by many major players, such as IBM, Intel and Accenture.

Things to keep an eye on

Hyperledger aims to define the underlying frame for ensuring interoperability and transparency of blockchain technologies. While there is an increasing number of organisations backing the project, it is interesting to see what kinds of services and applications will eventually be built on top of the common framework. Collaboration or cooperation between other general implementations of blockchain such as Ethereum are also something to keep an eye on.

Selected articles and websites

How the blockchain will radically transform the economy
Introduction to Hyperledger; Why open Blockchain is critical
Hyperledger vs. Ethereum: Yes? No? Maybe?
4 reasons why entrepreneurs should build blockchain companies
Deloitte Survey Results on Blockchain Across Industries

Mikko Dufva

Research Scientist VTT Technical Research Centre of Finland Ltd
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Voice interface

Why is this important?

As speech recognition gets better, it becomes more and more practical to communicate with a computer or smart device via voice. For platforms this means new possibilities and requirements when it comes to designing the interface. Can the service be used through voice commands? What are the new use cases when the user doesn’t have to stare at a screen?

Things to keep an eye on

Improved speech recognition and text-to-speech services means that the border between voice and text blurs. You can have a chat where one person is speaking and the other typing. This also means that everything that is said can more easily be analysed, which raises concerns for privacy. On the other hand, voice controlled digital assistants such as Siri or Alexa become the contact point for users and thus have an influence on which service or platform is used: for example, if Siri is told to play a song, it will more likely do it via Apple Music than Spotify.

Selected articles and websites

The next mobile interface: when bots and voice merge
Voice Is the New OS: Getting Ready for the AI-First World
Voice is chat’s next battleground
Bots, Chat, Voice, Zero UI, and the future of Mobile Apps

Mikko Dufva

Research Scientist VTT Technical Research Centre of Finland Ltd
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Deep learning and neural networks

Deep learning refers to an approach in machine learning, which aims at teaching machines to recognise abstract concepts based on large datasets. The leading edge currently is unsupervised machine learning, where the machine is left to make sense of the data on its own. Deep learning has made huge leaps in pattern recognition possible. Google Deepmind is one of the prominent companies utilising deep learning.

Why is this important?

For platforms deep learning offers the possibility to make sense of and recognise patterns from large amounts of data. Google provides an open source library called TensorFlow for this. Another benefit are the services that deep learning provides, such as voice recognition, chatbots etc. These can provide new functionality to the platform. On a broader view, the motivation is to use the deep learning to solve global problems.

Things to keep an eye on

The focus is now especially on unsupervised machine learning and “differentiable neural computers”, which can make sense of complex structured data. Examples of what deep learning algorithms such as the Google DeepMind can do range from lip reading to advanced translation to making sense of a metro map. One interesting development is making APIs to enable artificial intelligence algorithms to play games such as Starcraft and learn through it. This also means that artificial intelligence might be the future user of a platform. The big question then is will it benefit or exploit the platform.

Selected articles and websites

DeepMind has conquered games, London’s Underground and now it wants to help save the planet
Deep Learning Papers
Google’s DeepMind AI Said to Outperform Professional Lip-Readers
Zero-Shot Translation with Google’s Multilingual Neural Machine Translation System
Google’s AI creates its own inhuman encryption
Google DeepMind to Use Blizzard’s StartCraft II for AI Research Platform
Differentiable neural computers

Mikko Dufva

Research Scientist VTT Technical Research Centre of Finland Ltd
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