The following narrative is a speculative exercise about possible future usages of social media technologies. It illustrates the work done in the ARTICONF project on how social media ecosystems better support social media activity, pro-social behaviour and the sharing economy.

PART 1 — The Platform

In 2030, as a European citizen, I will use a federated network that no single entity can monitor and control, allowing me to use my identifier, credentials, reputation and monetary tokens in different services within the network.

In this platform, users have control over personal data and content. It allows them to know the servers’ physical location and see, for example, if they are in GDPR-abiding regions (even when the user is not). In addition, the platform’s documentation regarding the legality and user data handling is easy to understand and navigate (e.g. terms of service, data processing agreement, sub-processors lists). The platform uses public-key cryptography to store data and content in encrypted formats. Users can decide to be the only entity to retain the keys to decrypt it and share data and content to selected users only. No one else can get access, including service providers or platform maintainers.

The platform rewards participation fairly and transparently by storing all records, including all user actions and events, in a blockchain. These records are also immutable and resist manipulation. The platform also supports smart contracts and automatically executes them (i.e. perform a transaction, monitor information, document an event), allowing one to program and automate exchanges and actions, specifying the terms of the agreements in advance, according to one’s preferences. The system also provides information about other deployed contracts and uses this information to make predictions about possible future optimised strategies.

Finally, the platform also allows user participation in the collaborative moderation of social media services through content rating combined with machine learning tools and external sources such as independent fact-checker individuals. Besides, automatically calculated reputation scores reward users who create content or participate in its curation. Pseudonymous identities protect privacy while still allowing reputation calculations. In addition, automatic community detection based on content and not on users maintains user privacy.

PART 2 — The Concert Day

I’m travelling to an event later today, but I use my smart renewable energy production app to sell electricity on the marketplace before I go. Since I won’t be home, I can sell all the surplus production. I simply stipulate the energy needs of my fridge, set a price for the electricity I want to sell and even decrease the cost over time if nobody buys it. Smart contracts allow me to do this by updating my trading preferences under my energy profile, giving me complete control over the exchange. Other people do the same for buying energy and automatically purchase when it meets their price standards. The energy trading automated by the smart contracts will validate the trading condition as per user selling or buying preferences. The system uses this advanced information to predict the present and future demand and give recommendations about price and timings that ensure optimised return. For example, if it’s a sunny weather forecast, one can expect to earn good money from solar panels.

While using the carsharing and carpooling app to go to the train station, I see someone driving there from a nearby place. Although I don’t know this person, she has a good driver reputation score, so I trust to request her to pick me up. After receiving my request to share the travel and checking my reputation, she immediately accepts me as a passenger and shares all the costs for the trip among the vehicle occupants. My renewable energy production history indicates a good sustainability reputation, and the platform rewards me a discount. Great! She will be here in 10 minutes. When I arrive at the train station, I say goodbye to the driver and thank her for the friendly chat. Her driving was also excellent – I got to the station sooner than expected, feeling perfectly safe the whole time – so I gave her a high driver score. 

Once I get off the train, I realise I can use a similar carsharing service to go to the venue where my favourite band is playing. The band is trendy, and the concert attracts lots of people. Luckily, the carsharing and carpooling platform helped car owners and drivers to deploy the fleet close to the train station and transport hubs. I can predict the price, journey time and even look for available eco-friendly cars. I can choose how to optimise these travel metrics – for example, by first taking another train to the city centre and getting my ride from there rather than from the central station.

I arrive at the concert on time by spending less money and generating fewer carbon emissions. When the band starts playing my favourite song, I film myself and the band. Since the band is very famous, I placed this clip in a crowd journalism app. A few moments later, I receive the notification that someone bought the clip. Later, a friend messaged me to say that the evening news broadcasted my clip. Anyone could watch the clip for free, but I set its broadcasting rights price to the value I paid for the ticket and the train. I, therefore, enjoyed a free trip and concert.

Finally, I use my video opinion discussion app to join a conversation about the concert. I contribute to other people’s videos by adding and editing their closed captions, thus increasing my participation reputation score. I also add my review, praising the band’s excellent performance! My reputation score in the musical commentary is relatively high, and several people responded to my opinion video. Since I commented on a discussion directly related to the concert, the event organisers can easily find my contribution and reward me for it. I hope to get a personalised video response from the band that usually responds to the top video comments.

This blog post was written by the University of Edinburg team.

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