Cronycle Topics & Influencer Communities

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Cronycle is an information workflow application powered by Right Relevance (subsidiary of Cronycle), which is a topical information search and relevance platform.

Topics and Influencers (per topic) form the backbone of the search and relevance technology.

  1. Topics (over 50 thousand) including metadata like related topics & semantics like synonyms, acronyms.
  2. Topical influencers (over 2.5M) with score and rank.

Topics are identified by algorithmically mining over 10M unstructured documents on the web and leveraging Wikipedia and Right Relevance topical graph neighborhood techniques. Relationships and semantics are derived from this process with manual corrections and injections for the last mile.

Topical Influencers mining is fully algorithmic and primarily graph based. The methodology leverages ML, semantic analysis and NLP on unstructured data at scale and involves a 2-level proprietary people rank (custom page rank for social graphs):

Stage 1. Global PR to reduce a ~300M nodes graph to ~6M (for now) globally ranked influencers. This is a first level reduction and we don’t expose the scores. It doesn’t have topical context.

Stage 2. Graph partitioning of the ~6M connected nodes from stage 1 across our ~50K structured topic space using unstructured data assigned to each node. This leads to ~50K per topic sub-graphs, where a secondary PR is applied to determine the topic score for each node in each topical sub-graph. This secondary PR score is normalized to calculate the Right Relevance topic score and rank influencers for every structured topic in our platform. 

Our custom PR algorithm is derived from google pagerank but is specialized for social graphs (instead of links/webpages) with many important differences applicable to social networks.

The RightRelevance score of an expert/influencer for a TOPIC represents the authority within the topical community say for e.g. ‘machine learning’ of that influencer. This measure of influence per topic is termed as ‘topical influence’ and the topical communities formed are termed as “Tribes“.

Once we have the scored and ranked influencers’ community for a particular topic (e.g. machine learning, behavioral science, big data, emergency medicine, oil and gas, angularjs,  social media marketing etc.) we mine the web for content. The numeric influence from topics and influencers is inductively applied to this content for measuring relevance and forms a critical part of the search. We download ~600K articles daily from ~2M websites every month. Topical content and information are available in the form of articles, videos and conversations.

Points to note:

  • We dampen followers count, tweet count etc. noisy signals and lay much more focus on the topical network itself.
  • Each influencer can be part of multiple topical sub-graphs aka communities and have a different score, and rank, within each. This is exposed in our apps via scored tags.
  • Other, non structured, topics work via free-form search but the relevance may not be of the same quality. This can be seen by the score ’10’, which, probably poorly done, means we didn’t find a community for the topic.

Both topics and influencer graphs are mined and built algorithmically at scale with ever-increasing quality after every iteration.

Event: mastering information in a Trump Twittersphere

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We are hosting an event at the Century Club (61-63 Shaftesbury Ave, London) to discuss how Twitter is gaining importance in financial markets.  We will show you how hedge fund managers and analyst are using Cronycle (www.cronycle.com) and RightRelevance (https://www.rightrelevance.com/search/articles?query=crude%20oil – on crude oil for example) to keep ahead.

Please RSVP at [email protected]

We look forward to seeing you there.

Date:  9 July, 2018

Tine:  6pm onwards

Venue:  Century Club, 61-63 Shaftesbury Avenue

 

 

How Will Mobile Apps Make Business Easier

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The field of mobile apps is growing as we speak, mostly in two different ways. One way is the app development market that employs millions of people globally. The other way mobile apps affect the modern business realm is their use and application (sic!) for various business purposes. As new technologies are being developed, they’re also finding their way to mobile implementation. So, let’s read a bit more about the further potential of mobile apps in the world of AI, AR and other tech innovations.

 

1) Artificial intelligence and mobile apps

Smartphones, tablets, and wearables already function via smart software tools that can learn some of the patterns established by their users. However, this is only the tip of an iceberg. In other words, AI will change the market of mobile apps.

For starters, our living and work habits will be memorized and gathered by the means of AI. In turn, this will enable their creators and mobile providers to prepare various ready-made offers for our daily routines. Since many of our decisions and actions will be anticipated, all these tech innovations should lead to a more productive work day and well-organized free time.

Apart from that, app developers will have a chance to use these AI-collected data to do QA testing. As a result, they’ll save more time that can be invested in solving complex UX and functionality problems. AI features will be here to do the tiring coding tasks and analyze the UX-input gathered from customers.

Nevertheless, all these innovations could have negative effects on our privacy if our private data aren’t collected and stored in accordance with the legal guidelines. That’s why every app developer will need to take into consideration the GDPR act. Still, if you follow these rules, you’ll benefit from these tech innovations, including the AI-features.

 

2) Augmented reality in business apps

The growth of eCommerce industry has taken the global retail market by storm. Most renowned vendors already use apps, in addition to their business websites, to make their products available for shopping on the go.

Things are moving even faster today, especially with the introduction of augmented reality in eCommerce.

The greatest benefit of AR in this context is the ability to use its features to make shopping even simpler and less expensive for customers. For instance, Amazon has introduced AR-features in their app. What you can do here is simply project the item you’d like to buy on this website in the space you’d like to place it.

Similarly, car dealers are also taking the plunge into AR in their everyday work. Car buyers don’t have to go round countless car shops these days. They can simply use AR-features via dealers’ mobile apps to try new vehicles. Read more about these AR-trends in the article on The Drum website.

The downside of AR is that it’s still expensive for many SMBs. However, this will change sooner than we might expect, which will enhance the productivity of smaller business enterprises.

 

3) Accounting benefits of mobile apps

Small business owners often have issues with accounting demands. From their in-house books to bank accounts, to tax returns, more often than not they omit to process some data. These mistakes can result in inaccurate accounting data and financial penalties from the tax authorities.

The good news is that there are literally thousands of accounting mobile apps that will make your business life easier.

Still, this large number of apps calls for caution. Naturally, the best way to avoid any risks in this field is to use the mainstream apps, such as QuickBooks or FreshBooks. Both these tools have top-notch apps, plus they also have distinguished cloud features which makes them perfect for new business owners.

Apart from that, you can use modern accounting tools on your phone to simplify the payment procedure. In line with that, it’s wise to keep an online invoice maker at the touch of a finger. Every time you need to cope with larger orders or payments, you can issue an invoice in no time and speed up the purchase.

 

4) Increased productivity with mobile apps

Mobile apps have already improved our work productivity. Take only the accounting apps described in the previous paragraph. If you can use them on your mobile on the go, they enable you to deal with the business paperwork when commuting home from work or when you’re waiting in line in a supermarket.

Moreover, mobile apps enable SMB-owners and their workers to constantly communicate about their projects. What’s more, many project management tools come with mobile apps, as well. So, you have all-in-one solutions for work organization, time management and data share. Now imagine how advanced all these tools will get when AI, AR and other cutting-edge tech features become fully implemented in them.

Also, using mobile apps in various business ventures enables their owners and employees to collaborate remotely. This option opens an immense number of possibilities for employment, cooperation and better connectivity in terms of business productivity and operability. In the future, these features will lead to further improvements when it comes to work conditions and efficiency.

 

Conclusion

The number of mobile users is already counted in billions. The advancements in the production of smart devices and apps will lead to further growth in these figures. The improvements of mobile apps develop simultaneously with the number of mobile users. The combo of these two trends will produce a more engaging and inspiring work environment in the future, which will yield benefits for business owners, their employees, and, finally, the users of their services. That’s why we should all be looking forward to the app-enhanced business future.

 

This blog post was written by our guest,  Mark who is a biz-dev hero at Invoicebus which you can also follow on Twitter

Prediction Markets- How Can They Affect Us?

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Every time you enter a contract where you have to buy something in the future, you are entering a ‘futures contract.’ Where you agree to sell an item in the future because you think it will be more valuable, that’s a prediction market. Lately, prediction markets have been on the rise in both stocks and cryptocurrencies, and different investors have had divergent opinions.

How Prediction Markets work

In the stocks and commodities industry and even with Bitcoin as well, prediction markets are standardized. Each prediction contract made is specific to all the parameters involved. In a typical prediction market, the contract must specify the following:

  • The unit being traded
  • How the settlement will be made
  • The currency to be used
  • The quality of items being traded and the amount being traded

In the cryptocurrency sector, futures have been changing the way investors approach the cryptocurrency. Prediction markets allow investors to predict Bitcoin’s prices without even owning it. While this may be good news for traders who want to avoid the hassles involved with owning the cryptocurrency, it lowers Bitcoin’s liquidity.

Cryptocurrencies naturally increase in value as their demand goes up. However, if investors are able to invest in a coin without ‘physically’ owning it, this means that Bitcoin is actually not having increased adoption.

Do Prediction Markets Affect Cryptocurrencies Negatively?

Bitcoin prediction markets became popular late in 2017 after the Chicago Board Options Exchange (CBOE) introduced the concept on their exchange. One day after the announcement, Bitcoin’s price surged by 10%.

Within two weeks, top cryptocurrency exchanges like GDAX, Kraken, HitBTC, and Bitstamp also introduced prediction markets, driving Bitcoin’s value upwards to hit an all-time high of $19,000. When the futures contracts matured, something expected happened: Bitcoin’s value dropped by 72% within the first two weeks of January 2018, settling at $6,000.

Today, Bitcoin’s price is valued at the same range it was prior to the introduction of futures, $7,700. The introduction of prediction markets may have driven Bitcoin’s value upwards, but the price later underwent a market correction.

Although prediction markets affected Bitcoin’s price and a correction later happened, forces other than futures seems to have more impact on the price of Bitcoin. Read this article to learn more about prediction markets in the cryptocurrency industry.

Effects of Prediction Markets in General

Short-term Rise in Value

One of the most consistent changes noticed after the introduction of prediction markets in any industry is that the value of commodities involved increase suddenly. When gold futures were introduced in 1974, the price surged from less than $300 for a kilo of gold to $400 in just three months. Three months later, gold’s value went down again, probably because people dumped the asset.

In nearly all markets, the introduction of futures almost always leads to more demand for the commodity. However, after investors sell their futures contracts, a market correction occurs.

Demand for Commodities

Prediction markets may be a specialty of the experienced investor, but they always tend to drive demand for commodities to a great extent. Investors love to make predictions, and if they are certain they could make money out of it, they will purchase the commodity involved.

Bitcoin, for example, was valued at just above $7,400 when rumors emerged that the Chicago Board Exchange would introduce Bitcoin futures. Within a week of the rumors, Bitcoin’s value had risen to more than $10,000. Many institutional investors, who previously have always been wary of cryptocurrencies, quickly adopted the cryptocurrency.

High Volatility

With extremely high demand for any product comes a market correction. This has occurred and reoccurred in different stock markets, commodities and with Bitcoin as well. Last year, when Bitcoin moved from just $7000 to $19000 in one month, its price suddenly moved down to $6000 in the next 30 days.

If today a cryptocurrency exchange announces that they will offer prediction markets for a less popular coin like Zcash, its demand will suddenly increase. However, once they buy contracts and they mature, the coin’s value is likely to go back once again, leading to huge profits or losses to those on the wrong side of prediction markets.

Greater Convenience for Investors

Prediction markets are a breath of fresh air for many investors. For one, futures are conducted in the most convenient manner for investors. If the markets are made for commodities like gold, investors only need to sign contracts using their cash. They don’t have to own physical gold to enter futures contracts.

With more investors feeling confident about trading, demand for the commodities definitely increase. In the long term, prediction markets tend to improve the liquidity of commodities and assets. However, as studies have often shown, they don’t have a great impact on any industry on their own. Traditional forces of demand and supply have the biggest impact on the prices of commodities and digital assets.

Disrupting Industries

Like most financial instruments, prediction markets keep on evolving. In sports and casino gambling, it’s now possible to make predictions of live events so that your contract matures within minutes or hours. For example, you can bet the outcome of a basketball game while it happens.

In the blockchain industry, prediction markets are evolving by eliminating the intermediary companies. Instead of making predictions on a website, different investors can predict the outcome of games, events or market prices directly on a blockchain platform. Their funds are held by smart contracts, and winners get their rewards automatically after the outcome of the event is determined.

Information Gathering

One of the most underrated impacts of prediction markets is their ability to influence people’s decisions. If a market asks people to bet against the outcome of a football game and 70% of the investors predict team A will win, other investors are likely to place the same bet.

If 80% of investors make a prediction that certain crypto will drop in value, a lot of investors are likely to short sell the same coin because of the influence of prediction markets. On a broader scale, prediction markets have always been used as the benchmark of making financial decisions by lots of companies, governments, and investors.

In Conclusion

Prediction markets, like any financial instruments, may have an impact on trading markets from time to time. However, on their own, these markets don’t have such a huge impact as to affect the long-term price movements of stocks, assets or commodities.

 

This blog post was written by our guest, Ronny Martelli from Exposureland.com

How AI Can Improve Customer Engagement

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How AI Can Improve Customer Engagement

Success in business can be measured in happy customers. Aside from your product or service offerings, showing consumers you appreciate them, hear them, and are interested in providing them with the best customer service possible, will not only help you retain current customers but also gain new ones. This, in short, is called good “customer engagement”. Various methods and tools have become available in recent years to best optimize customer engagement. The most recent game changer has come in the form of artificial intelligence. Because AI can provide tremendous benefits with minimal effort, businesses of all sizes, in various fields, are taking full advantage of what it has to offer. In fact, according to a Pegasystems survey on customer engagement, one hundred percent of top-performing companies are currently using AI in some fashion. For those interested in following that lead, we’re outlining ways in which AI can improve customer engagement.

Though the general public may not be entirely aware of it, use of AI is already incredibly common. While only thirty-four percent of people think they use AI, the reality is that eighty-four percent of us are interacting with some form of artificial intelligence on a daily basis. This statistic is good news when it comes to placating consumers who fear or negatively view the use of AI in business. Considering the technology can hugely benefit a consumer’s experience, education is key. From better product offers to faster response times and more relevant messaging, AI’s power to anticipate and meet customer needs is a win for us all.

Properly engaging with your customers begins with understanding them. Knowing the answer to a few simple questions such as: who they are, what they want, what they can afford, their pain-points, and what platforms they communicate on; gives you a running start to improved connections. Through machine learning and AI technology companies are capable of collecting and analysing enormous amounts of data that can provide the answers to these questions to create better customer experiences with each interaction.

An increasingly popular tool for bettering customer engagement is the chatbot. These virtual assistants go hand-in-hand with customer service as more and more companies recognize their value and begin implementing them.

Rapid Response

Unlike human customer service representatives, chatbots can work 24/7 and are capable of handling a high volume of requests without the need to spend time searching for answers. This helps reduce service time up to fivefold, improving customer support, and reducing operating costs by as much as sixty six percent.

Proactive Interaction

Typically, companies engage with customers passively, responding to inquiries rather than starting them. Chatbots reopen the gates of communication by beginning conversations on their own, and share useful information with customers. Things like new product offers, blog entries and so on. Over time, this leads to greater personalization as Chatbots take in personal information on a customer, and offer them more targeted suggestions.

Another aspect of improved customer engagement is hyper-personalization. Consumers today want to feel connected to the brands they buy from and you can meet that request by leveraging AI. Capturing data on prospects is nothing new for businesses, however with AI and machine learning marketers can analyze current and historical facts to perfectly structure the most relevant message to each individual. Knowing what customers are thinking and saying about your brand creates opportunities for engaging those consumers on the topics they’re interested in, while communicating through the platform they prefer.

Particularly with a younger audience, positive customer engagement is essential. Well-educated on technology, the younger generations know what businesses are capable of, and because of that, they expect authentic, meaningful, and responsive interactions. AI can help you meet these needs effectively and efficiently resolving complaints and inquiries 24-hours a day.

 

The guest post was written by Sara a.k.a. Digital Diva, Co-founder of Enlightened Digital who you can follow as well on Twitter.

What will be left of Bitcoin when the hype ends

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There is a great deal of real value in some cryptocurrency technology

There are a number of overlapping technologies involved in understanding cryptocurrencies. Currency itself is a concept which people deal with every day but may not have considered more deeply than the level required to transact a purchase. Behind cryptocurrencies lie blockchains, a second level of detail. There are now cryptocurrency phones, which connect to standard phone networks using standard data plans and can help you conduct your next generation currency trading from wherever you happen to be. These things are all happening at the same time as other technological marvels – from The Internet Of Things, to 5G, Artificial Intelligence (AI) and beyond. It can hardly be a surprise when people turn off from considering these things, given the overlapping complexity they present.

Few doubt that much of the talk in the media and industry is based on hype around these new technologies. The question is, where does the real value begin. And sitting underneath Bitcoin and its competitors (the 1500 or so direct alternative cryptocurrencies that Bitcoin has.)

The real value when Bitcoin is done is in Blockchains

A Blockchain is simply a distributed ledger  a list of who owns what asset, which is stored in multiple places – on multiple computers – at once. The distributed nature of the chain is what give them their value. At a principal level, Blockchains serve many of the purposes that banks currently do, they provided a medium both ends of a transaction can trust to act fairly. They also neatly sidestep many of the problematic aspects of banking, however. They can perform a host of useful functions beyond recording who owns what Bitcoin. They are hard to hack, for example – because hacking them would require multiple parallel successful attacks (on every blockchain miner in the system at once.)

Blockchains can have intelligence and decision making built in to them, in a way that current asset ledgers do not. Since they are computer and therefore algorithmically based, ‘IF / THEN’ statements can be built in to them – so called ‘smart contracts’. For example, once a Blockchain received a reliable notification that ‘money has been paid’ and ‘identity is confirmed’, they could transact legal ownership of an asset such as a house. This sort of facility cuts out a collection of middlemen, within the housing chain, and provides transparently reasonable terms, which cannot be interfered with and with which everyone involved can agree, before the process starts.

Blockchains then are more useful than cryptocurrencies and are likely to be around long after Bitcoin has been relegated to the bubbles of history. Cryptocurrencies require a Blockchain to survive, but a Blockchain does not require a cryptocurrency to function.

Where could I invest in Blockchains?

Ripple is the most successful Blockchain company in the world at the moment. The publicly traded company has seen its share price grow even more than Bitcoin’s value, following successful trials of their technology. It’s not hard to imagine Ripple, or another Blockchain product being used to store and provide reliable proof of some of the most valuable and currently difficult to manage aspects of our lives.

A Ripple Blockchain could be used, for example, to provide proof of identity with a digital passport, digital birth certificates or digital driving license. Other assets, like car ownership, could also be stored in a Blockchain making them easier to transact and cheaper to administer. Governments will be particularly interested in lowering the cost of overseeing these key life documents.

Blockchains are not, however, a panacea. As they stand have one major drawback – the enormous amount of energy and reasonable amount of time required to transact something through them. Solutions are being worked on.

Bringing it all together

Even Warren Buffet has called Bitcoin ‘Rat poison squared’. Buffet is one of the world’s smartest and most consistently successful investors but he is saying something which is common sense. Cryptocurrencies essentially amount to private companies printing the sovereign currencies of the countries of the world. When Bitcoin sells $3bn of cryptocurrency, they are effectively adding that amount to the money supply. Bitcoins are also much harder to tax than existing currencies. Governments simply will not allow private companies to produce currencies which undermine their ability to usefully influence the

Given the huge profits made by many of the world’s banks, regulators in key countries are closely watching Blockchains to offer some long needed innovation in the field. Long after Bitcoin has crashed, Blockchains will be around and providing real, measurable value, to the economy and us.

 

This guest post was written by Ralf Llanasas from What Phone.

Is Facebook going the way of Bell? Don’t bet on it

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America’s industrial scene has long been marked by monopolies – and by government, attempts to break them and ensure fair trade. Rockefeller’s Standard Oil, once the world’s largest oil company, found itself facing that economic reality in 1911 when the Senate at last succeeded in an anti-trust lawsuit. With Facebook in the crosshairs from both sides of the political aisle, there have been suggestions that the social media giant might be just be too big to stand as well. As South Carolina Senator Lindsey Graham argued to Mark Zuckerberg over his two day hearing on Capitol Hill, Facebook’s spread across apps and platforms makes it feel discomfortingly close to a monopoly (even if Zuckerberg feels otherwise).

Yet in the tech industry, there’s a better example of a monopoly which escaped the hatchet: Bell Systems, which for over a century held sway over American telephony. Unlike Standard Oil, which had sought to fight the government, Bell was smart enough to ask to be regulated. In return for cutting off parts of their enterprise, they got to maintain their monopoly until 1983. Not bad going, all things considered.

A government-regulated monopoly on Facebook would be beneficial for both parties. Facebook would get to keep on keeping out the competition. The US government would be able to have the peace of mind that they were regulating the biggest source of their citizens’ data outside of their own servers. And that’s not even considering that regulation would almost certainly offer a backdoor for accessing said data for national security purposes.

There’s also that fact that regulation avoids one danger of a break-up: strengthening Chinese tech companies. That was seen as such a trump card that it made its way onto the notes that Zuckerberg brought to the first day of his hearing. It’s a fair point, perfectly played to America’s policymakers with their endless references to Facebook as an ‘American company’. Given the lack of a Western competitor, China’s all-in-one WeChat (artificially grown in a state capitalist vacuum) could have the utility and the clout to take over at least some of Facebook’s roles. For US politicians, the idea of a company with close links to China’s government is probably even less appealing than a company with dubious links to Russia’s.

Of course, Bell was dealing with telephones and telegrams: simpler technology, and far easier for a government to wrap its head around than social media, data protection, leaks, and so on. The level of technical expertise on offer at Zuckerberg’s hearings in the States, in general, has not been the most impressive. What form the regulation would take is also difficult to see: perhaps monitoring of the types of data shared with third parties and available to Facebook employees themselves.

That still leaves the question of political division. Whilst concerns about Facebook are shared across the spectrum, the reasons for those concerns are not. Democratic politicians attacked Zuckerberg largely on Russian interference and the use of the site’s advertising platform for discrimination. Republicans routinely claimed that conservatives were being censored, with live-bloggers Diamond and Silk repeatedly being presented to Zuckerberg as victims of his site’s liberal agenda. Moving towards a consensus – beyond agreeing that Facebook has made a colossal blunder – seems almost inconceivable.

And finally, there’s the fact that this should have been a chance to grill a man in charge of the company which handed over immense amounts of data to dubious researchers and even more shady firms – whilst instead, we got more than a little bonhomie. Between the struggles of lawmakers to actually understand what Facebook does, and the rare cases of tough questioning that didn’t allow Zuckerberg to return to his script, there was far too much bonhomie: asides asking for rural internet, offering top tips for recruiting spots, even the outrageous attempt to curry favour by stating that Zuckerberg’s alma mater in Westchester, New York, was proud of him. In what were nominally occasions in which Mark Zuckerberg was to be cut down to size, America’s politicians made clear Big Tech’s immense staying power. The lure of an industry which offers jobs and money – and re-election – was too big, apparently.

Facebook has, for a long time, not been a product which people show real excitement about. Millennials, the hip generation for platforms, have increasingly voted with their feet or are vocal that they view it as a tool for keeping in touch with family. And yet, despite all the bad press and Silicon Valley screw-ups, the site has continued to hold on and grow. The immense fines from GDPR might hurt it enough to force a rethink of redirection, but don’t expect action from America’s politicians, too in thrall to the seductive power, money, and jobs of Big Tech.

How App Developers Are Planning To Employ AI To Enhance Mobile App Development

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Despite being regarded as an emerging technology, it is quite interesting to see how artificial intelligence (AI) is influencing mobile application development, impacting the way people communicate, affecting the society, and probably changing the world. Obviously, the growth of artificial intelligence is already causing a transformative change in the application development space. No doubt, if everything that this emerging technology development is believed to accomplish turns out to become a reality, then it will surely have a huge impact on human lives.

It’s no secret that despite the giant strides achieved in the mobile industry with app development, Indian app developers are still having a hard time meeting internal demands for building applications. In a bid to effectively streamline programming and meet business needs and demands, several application development teams in India are already augmenting their efforts with co-developers of AI to not only enhance growth and development in the industry but to also ensure effective data cleansing and organization, agile product management, and quality assurance.

As part of efforts to enable Indian app developers to focus on design and development tasks that are more closely related to users’ needs, artificial intelligence co-developers are stepping in to handle low-level routine tasks like infrastructure and other peripheral tasks. However, there is every tendency for this new emerging technology to take on much higher-level work in the nearest future. Here are some common areas of app development in which artificial intelligence (AI) would flourish in years to come.

 

Application development

Just so you know, many Indian app developers are already getting involved with the use of AI to enhance application development. Basically, this new initiative is helping to transform the way and manner most app development companies run their development processes. Though they’ve not gotten there yet, it is obvious that mobile application developers are on the right path to employing AI to automate quality assurance (QA).

This implies that in the nearest future, apps will be able to run tests on themselves, identify bugs and get them fixed with very little direct input from users. Some Indian app developers opine that this new technology will allow apps to be able to modify and run updates that can better suit any changes or updates regularly performed by an operating system (OS). Basically, this will help to cut down costs significantly as such self-optimizing apps will be able to transform themselves to function efficiently with the firmware updates of any mobile device.

 

User Experience (UX)

It may interest you to know that for several years now, artificial intelligence (AI) have been available. However, the technology had not attained the level of impacting lives directly until now. Nevertheless, there is still much to achieve with AI as this is not exactly how it is expected to function. Until it gets to the true next-gen version there is still very much for developers to achieve.

Apart from impacting the development of apps, AI is also affecting user experience. Though at the moment, achieving this is still not close possible, however, there is so much developers can do with AI particularly when it comes transforming user experience (UX). Before now, tech devices such as PCs were designed to work on users’ instruction – i.e. they can only perform based on what they are commanded to do. But when AI begins to identify those things humans want to do and does them without any intrusion then things will begin to turn around.

Imagine an AI-powered app that watches a user’s privacy actively. While it is not overly intrusive or strict, it is capable of monitoring events and actions of other applications on a device and can even get to know when these apps are trying to retrieve the information they do not want to share. In a bid to get other devices in the know as to what services are currently ongoing, artificial intelligence will enable other applications installed on a user’s device to ascertain what the user wants to do such as searching for a location to visit so that push notifications about special destinations and hotels can be necessarily forwarded for consideration.

 

Automation

Since people are more concerned about making a living, automation of jobs has been on the job radar making headlines. With AI, Indian app developers will be able to effectively integrate machine learning into the app development process to automate code preparation, validation, and generation. With this development, developers and designers will spend quality time solving difficult tasks rather than spending time on coding. Basically, it’s all about making smart devices think by getting them integrated with sophisticated artificial intelligence.

No doubt, there seem to be much to expect from artificial intelligence and with such promises, achieving these does not appear any easy for Indian app developers. First and foremost, mobile application developers need to understand clearly what AI-enabled apps have to offer both from the structural and marketing standpoint. In today’s competitive world, it is highly significant for app developers to meet the users’ requirement or demand to ensure adequate compliance. To this end, there is every need for programmers to be highly flexible in developing these apps.

 

What does the future hold?

Though AI can be said to be currently out of the state of infancy, as there is already an overwhelming interest from many companies looking to develop their apps with it, however, it is important for Indian app developers to know that the emerging technology is still on the process of maturing. Programmers can expect the use of chatbots to mature relatively quickly in the coming years as they are better constrained and deal more with text interactions than interactive voice response (IVR) that deals with voice recognition.

Ultimately, it is the dream of every modern app developer to write apps for smart devices with algorithms that adjust based on observed behavior. Though there is still very much work to be done on this, it is good to know that the turning point or point of change is near, as developers are not relenting in any way to create efficient AI-driven apps.

 

This guest post was written by Kenneth Evans from Top App Development CompaniesYou can follow more on Twitter from Kenneth and Top App.

Russia and the West: what is the Endgame?

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In light of the poisoning of the former Russian spy Sergei Skripal and his daughter Yulia, and the tit-for-tat expulsions of diplomats by NATO countries and Russia that followed, one might begin to wonder: what exactly is the endgame of this increasing confrontation between Russia and the West?

The number of Russian diplomats that have just been expelled from NATO countries

When Prime Minister Theresa May announced the initial expulsion of 23 Russian diplomats, identified by British authorities as “undeclared intelligence officers”, the mood in the House of Commons was one of apparently sincere moral outrage. How dare Russia carry out such an attack on our soil! How can we punish the Putin regime to the maximum extent? From what most of the MPs had to say, one might conclude that their concerns were solely around the human rights record of Putin’s Russia.

Few would deny that Vladimir Putin is an authoritarian leader with scant regard for human rights, but there is no shortage of such leaders today on the world stage. The United Kingdom happily sells arms to Saudi Arabia, an absolute monarchy carrying out a brutal war on the Houthi rebels in Yemen and inflicting a terrible cost on that country’s civilian population. Britain rolls out the red carpet for Xi Jinping, now likely to be China’s dictator-for-life.

Perhaps the problem is that Putin’s ruthlessness is not confined to Russia’s borders, and extends as far as Britain’s shores. This argument lacks geopolitical perspective, however. Even after assurances were given to the Russians that NATO would not expand any further into what was formerly Russia’s sphere of influence, that organisation, redundant after the fall of Soviet Communism, went on to expand right up to the Russian border with Estonia and Latvia. While both the West and Russia have interfered in Ukraine’s affairs, to the detriment of Ukrainians, it should be obvious that the latter has a much greater interest in what transpires in that country. Even in further-flung Syria, Russia has many military assets as well as a decades-old alliance with the Assad regime. The West, meanwhile, has effectively supported radical Islamist groups in an effort to overthrow Assad, having failed to learn from its mistakes in Iraq and Libya.

The West cannot accuse Russia of playing realpolitik when it does so itself, under the guise of humanitarian intervention or democracy promotion. Put another way, it is not military intervention per se that the Western establishment opposes; it is military intervention by an outside power, in service of its national interest rather than that of “the liberal international order”. Russia as a nation state stubbornly refuses to go quietly into the night and let the “end of history” dawn .

Even the poisoning of the Skripals looks more like a pretext to pursue anti-Russia policies, instead of the real cause. Skripal was a double agent, and spies put their lives on the line. More inexcusable is the careless way in which he was targeted, putting his daughter’s as well as other innocent lives at risk. However, one has to be rather naïve to think that that MI6 has never endangered or harmed any innocent people during its various activities abroad.

What really seems to lie behind the hostility towards Russia is the overblown idea–verging on a conspiracy theory–that without malicious Russian cyber-activity, Brexit, the Trump presidency, Catalan separatism, virtually any unwelcome political development in the West that one cares to name… would not have happened. This is not to deny that Russia tried to interfere in elections by spreading propaganda. The United States has long engaged in similar activity and continues to do so this day, as former CIA director James Woolsey admitted in a recent television interview. The problem, however, is that Russia is blamed disproportionately or even entirely for certain political outcomes that might have come to pass anyway. Russia did not create the economic grievances, social divisions and culture wars that characterise the contemporary West; the most that can be said is that it–along with many other actors–moved to exploit them where possible. In other words, Russia is a scapegoat. The process of scapegoating is driven by sentiment, rather than reason. Unfortunately, this means that the current policy of confrontation with Russia has not been rationally thought out. If it had been, it would have been seen for the madness that it is.

Firstly, it has not in fact been proven that the Salisbury attack was carried out by “the Russian state”. If indeed it was not, and the British government rushed to judgement, this would be highly irresponsible – especially given the stakes of a conflict with Russia. The fact that Jeremy Corbyn has pointed this out does not make it false.

Secondly, if tensions with Russia continue to escalate, it is difficult to see how they will be ratcheted down. One cannot simultaneously believe that Putin is an evil genius and that he will simply back down after the next round of sanctions. The more he is pushed into a corner, the more likely he is to take military action of some kind. And the truth is that the West no longer has much of a stomach for that. If this is true even of a military superpower like the United States, which now does much of its fighting with drones and avoids putting its own citizens in harm’s way, how much more so must it be true of the United Kingdom?

If Russia is as wicked an adversary as many in the Western elite appear to believe, why antagonise this nuclear power further? How can anyone imagine that embarking on such a course of action will end well?

3 April Update: Gary Aitkenhead, the head of Britain’s military research centre, the Defence Science and Technology Laboratory, was “unable yet to say whether the military-grade nerve agent that poisoned a Russian double-agent last month had been produced in Russia.”

#DeleteFacebook Isn’t About Data Security

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In the wake of the Cambridge Analytica scandal, Facebook might actually be in trouble. The #DeleteFacebook hashtag is trending, and it’s seen some unlikely contributors, like Blink 182 singer Mark Hoppus, and Brian Acton, the co-founder of WhatsApp, which was itself sold to Facebook. Meanwhile, Facebook stock has dropped by 10% this week so far. The FTC has announced that it’s opening an investigation into Facebook’s business practices, to determine whether Facebook violated its user agreement, an infraction which would come with a hefty fine. Mark Zuckerberg hasn’t made a public statement about the matter yet, but he’s been summoned by the UK Parliament. The bad news keeps piling up.

The obvious question is whether Facebook will survive, after whatever punitive measures are dispensed. And, while it’s possible that it won’t, it’s difficult to imagine how its extinction would come about. Its users could always leave, but there’s very little individual incentive to do that, and, given that a third of the world uses Facebook, getting everybody to quit would represent a massive coordination problem. Therefore, unless Facebook is banned outright, or somehow sued into oblivion, it seems likely that it will persist, if in some sort of regulated or otherwise curtailed form.

The less obvious question is: why now? This is by no means the only data scandal that Facebook has been embroiled in. Any intelligent consumer of digital media knows very well that Facebook is harnessing their personal data, and that such data has been treated carelessly before, and used for somewhat nefarious ends. Probably the most striking example came in 2014, when PNAS published a study by researchers who quite literally played with the emotions of Facebook users to find experimental evidence of Internet-based emotional contagion. More recently, earlier in March, it was revealed that Facebook’s researchers had told advertisers that it had figured out how to identify whether its teenage users were feeling desperate or depressed—and that this could be worthwhile marketing data. Given all of this, it’s clear that data security isn’t the primary force driving #DeleteFacebook.

It’s much more plausible that what’s behind the media conflagration isn’t data security itself, but rather the involvement of Donald Trump. Some have claimed that Cambridge Analytica was responsible for Trump’s election, having provided his campaign with personal data about voters that (maybe) offered unprecedented psychologiccal leverage, revealing which precise people could be viably targeted by propaganda. If you’re anti-Trump, and you believe this, then your beloved social network has unwittingly engaged in a large-scale erosion of democracy, which is to say, a technologically-driven coup by a candidate you don’t like.

This may not even be the case, by the way. The person who’s most loudly proclaimed that Cambridge Analytica was responsible for the election’s outcome is the now-suspended CEO of Cambridge Analytica, Alexander Nix. Ted Cruz’s campaign hired Cambridge Analytica, obviously didn’t win the election, and, as David A. Graham of the Atlantic reports, “found that CA’s products didn’t work very well, and complained that it was paying for a service that the company hadn’t yet built.” Corroborating this view is Kenneth Vogel, a New York Times reporter from their Washington Bureau, who recently Tweeted that Cambridge Analytica “…was (&is) an overpriced service that delivered little value to the TRUMP campaign.” He went on to claim that campaigns only signed up to secure access to the Mercer family—a rich line of big-time Republican donors—being that they’re major CA investors.

To sum up: Cambridge Analytica is only one of many organizations which have used personal Facebook data in a sinister manner, and its use of that data might have actually been inconsequential. If this is the case, #DeleteFacebook offers a clear lesson to tech companies, which is that it’s not actually important whether your product or service unscrupulously surveils its users. It’s more important to ensure that your company doesn’t give its data to anybody particularly unpopular, especially if they end up getting elected. If you sell your data to relatively unproblematic clients, you’ll probably be okay.

Cyborg Chess and What It Means

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When arguably the greatest chess player of all time, Garry Kasparov, was beaten by Deep Blue in 1997, some took it to mean that human intelligence had become irrelevant. For instance, Newsweek ran a cover story about the match with the headline “The Brain’s Last Stand.” However, the chess-related conflict between human and computer cognition turned out to be somewhat more convoluted than that.

In the wake of the match, Kasparov came up with a concept he called “Advanced Chess,” wherein computer engines would serve as assistants to human players—or the other way around, depending on your perspective. Kasparov’s idea was that humans could add their creativity and long-term strategic vision to the raw power of a computer munching through plausible-seeming variations. He thought that, perhaps, in long games, such cyborg teams could beat computers, complicating the idea that human intelligence had simply become obsolete.

He was right. Highly skilled cyborg players turned out to be stronger than computers alone. Most famously, in 2005, a cyborg team won a so-called “freestyle” tournament—one in which entrants could consist of any number of humans and/or computers. And, even more surprisingly, the tournament was won by a pair of relatively amateur players—Steven Cramton, and Zackary Stephen, both far, far below master strength. They came out on top of the powerful program Hydra, as well as esteemed grandmasters like GM Vladimir Dobrov. And the secret to their success seemed to be that they were the best operators—they had figured out the ideal way to enhance the chess engines’ intelligence with their own.

In other words, for the human half of a cyborg team, being a supremely good chess player wasn’t as important as knowing how to steer computer intelligence. AI manipulation was itself a relevant skill, and the most important one. Cramton and Stephen ran five different computer programs at once—both chess engines and databases which could check the position on the game board with historical games. Using this method, they could mimic the past performances of exceptional human players, play any moves that all the engines agreed upon, and more skeptically examine positions where the different engines disagreed upon the right way to proceed. Occasionally, they would even throw in a slightly subpar but offbeat move that one of the programs suggested, in order to psychologically disturb their opponents.

This is kind of a beautiful picture of computer-human interaction, in which humans use computers to accomplish cognitive tasks in much the same way that they use cars to accomplish transportation. However, there’s a strong possibility that this rosy picture won’t last for long. It’s possible that, eventually, chess engines will get strong enough that humans can’t possibly add anything to their strength, such that even strong operators like Cramton and Stephen would, if they tried to provide guidance, only detract from the computer’s expertise. In fact, this may have happened already.

In May of 2017, Garry Kasparov said in an interview with Tyler Cowen that he believed cyborg players were still stronger than engines alone. However, that was before Google’s AlphaZero chess engine, in December of 2017, absolutely destroyed a version of one of the world’s best chess programs, Stockfish. AlphaZero, which was grown out of a machine learning algorithm that played chess against itself 19.6 million times, won 28 out of the match’s 100 games, drew 72, and lost not one.

What was more notable even than AlphaZero’s supremacy was its style. AlphaZero played what seemed like playful, strange moves: it sacrificed pieces for hard-to-see advantages, and navigated into awkward, blocked-up positions that would’ve been shunned by other engines. Danish grandmaster Peter Heine Nielsen, upon reviewing the games, said “I always wondered how it would be if a superior species landed on earth and showed us how they play chess. I feel now I know.” If there’s any computer that’s exceeded the capacity of cyborg players, it’s probably AlphaZero.

This progression—from the emergence of strong AI, to the supremacy of cyborgs, to the more complete supremacy of even stronger AI—could pop up in other fields as well. Imagine, for example, a program, Psychiatron, which could diagnose a patient’s mood disorder based on a momentary scan of their face and voice, searching for telltale signs drawn from muscular flexion and vocal intonation. That program would make psychiatrists irrelevant in terms of diagnostic process.

However, you might still need a psychiatrist to make sense of Psychiatron’s diagnostic to the patient, and provide that patient with a holistic treatment that would best address the many factors behind their disease. Psychiatron would simply enable psychiatrists to be better. Eventually, though, that cyborg team might be superseded by an even stronger Psychiatron, which could instantly dispense the right series of loving words upon making a diagnosis, as well as a carefully co-ordinated package of medications and an appropriate exercise plan, all through machine learning techniques that would be completely opaque to any human operator.

This is a version of the future that’s either utopian or nightmarish depending on your perspective—one where we are, as Richard Brautigan wrote, “all watched over by machines of loving grace,” who, like parents, guide us through a world that we’ll never fully understand.

Cryptocurrencies and the True Source of Value

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One of the arguments against Bitcoin and cryptocurrencies in general is that they do not represent true value. Behind the crypto-algorithms, according to this line of argument, is really nothing that could objectively be considered currency; indeed, nothing at all. Hence, cryptocurrencies are a bubble which is bound to burst. This is not just an any-man-on-the-street opinion; it has been espoused by the billionaire investor Howard Marks, who predicted the “dotcom bubble” of the 1990s. “In my view, digital currencies are nothing but an unfounded fad (or perhaps even a pyramid scheme), based on a willingness to ascribe value to something that has little or none beyond what people will pay for it,” Marks said in 2017. Marks used historical precedent to underscore this point, pointing to the notorious “tulip mania” that started in the Netherlands in the 17th century. In 1637, at the height of the mania, a single tulip bulb could be worth up to ten times the annual income of a skilled craftsman.

Lydian coin. Inscription reads “I am the sign of Phanes”. Electrum (alloy of gold and silver), length: 2,3 cm. Late 7th century BCE, found at Ephesus. Israel Museum, Jerusalem.

One might wish to consider other historical precedents, however. Currencies per se are a surprisingly recent invention in human history. According to the archaeological record, the first coins were used in Lydia (present day Turkey) in the 7th century BCE (see image above). This is long after the rise of cities and kingdoms and indeed the successful smelting of metals, including gold, silver and bronze; even 500 years after the commencement of the Iron Age in the Middle East. We also know that this was not due to lack of technical engraving ability, since many small metal seals with intricate designs have been found dating from many centuries prior to the 7th century Lydian coins (see image below).

Seal of Tarkummuwa, King of Mera. Silver (diameter: 4.2 cm). c. 1400 BCE, found at Smyrna. Walters Art Gallery, Baltimore.

The anthropologist David Graeber has provided an interesting explanation of why coinage was eventually developed. Coins were not initially used by most ordinary people, he argues. The available archaeological evidence shows that the first coins were used by soldiers. This makes sense, Graeber argues, when we consider that ancient rulers had to find a reliable way of feeding armies at the frontier of their empires. If the soldiers were stationed inland, he points out, it would be extremely difficult to move large amounts of grain or other foodstuffs with them. If, however, standardised coins could be minted and given to soldiers, the soldiers would be able to buy the necessary food from the ruler’s civilian subjects in these far-flung parts of the empire. By taxing his subjects, these metallic tokens of value would then be returned to the king. They began as a more efficient way of feeding armies, but once they acquired universally recognised value within the state, could be applied to any economic transaction.

In order to be hard to forge, coins had to be minted out of rare metals by skilled craftsmen. But even gold, silver and copper, which were used for the earliest coins, have no intrinsic value, as Israeli historian Yuval Noah Harari points out – “you can’t eat it, or fashion tools or weapons out of it.” The lesson here is that no form of currency has value above and beyond what we ascribe to it, collectively, as human beings. Thus, it will not do to dismiss a cryptocurrency, as Marks does, because it has no value beyond what people will pay for it (this is not to say, of course, that other arguments against cryptocurrencies fail; only that this particular line of argument is unconvincing). One might well imagine an ancient Lydian exclaiming, “These bits of metal with their fancy designs and inscriptions have no real value. The whole fraud will surely collapse after the king dies.” And yet, as we now know, it did not turn out that way. The coins had value because enough people came to believe that they did and that was all that mattered.

We have since, although only relatively recently in 1971, abandoned the gold standard, making way for the the US dollar as the world’s reserve currency. One could even argue, as some have, that the dollar is a less reliable store of value than either gold or Bitcoin, because the US Federal Reserve can simply print as many units as it sees fit – and indeed, in the last round of quantitative easing since the 2008 crash, it has been printing an unprecedented number. The amount of gold in the world runs up against physical limitations, whereas the amount of Bitcoin runs up against mathematical ones. While it is true that other cryptocurrencies can avoid the same limitations that appear to be built into Bitcoin, matters such as the total number of units to be issued and the value of each unit relative to everything else still depend on the vital criterion of consensus by the community of users. Notice that the technological aspects aside, this criterion also applied to the very first currencies used by our species. While it is true that the first coins were issued by rulers in a top-down fashion, these rulers did not realise that they had brought into being a monetary system that would soon escape their control. As Graeber also notes, after appearing in Lydia, coinage soon emerged independently in differently parts of the world. This meant that when different empires came into contact with each other, they had to arrive at a fair exchange rate. If the empires were of roughly equal power, this could not be determined by either of their rulers and was determined instead by market factors beyond any one individual’s control. Exchange rates between different official currencies have thus continued to fluctuate from ancient until modern times.

Bitcoin and other cryptocurrencies could indeed be seen as the next logical step: prior to their emergence, the only “non-physical” medium of exchange resembling a truly global currency was the IMF’s “Special Drawing Rights” or SDRs, although as their name suggests these have only been issued and used in exceptional circumstances. Better yet, unlike SDRs, cryptocurrencies are not controlled centrally in any way. Instead, they are designed to bypass both governments and banks. All they require is a public ledger, the blockchain, to keep track of all transactional information. Governments and banks understandably find this frustrating and will likely do all they can to bring cryptocurrencies under their control. In this respect, however, they may resemble a Lydian king who tries to fix the prices of various commodities, only to find his attempts frustrated by his subjects, who find roundabout ways to buy or sell commodities at market prices.

The fact of the matter is that we are now all living in a global economy, and cryptocurrencies have beaten the IMF to the finish line of establishing imaginary units of value that are created (or “mined”), recognised and used globally. One or even all of them may collapse eventually, but the point is that such an event cannot be brought about by governments or banks. The technology is now out there, as is the will to avoid the fiats of governments or banks. And if they do collapse irreversibly, that is not necessarily good news for fiat currencies. The need for an independent global currency will likely persist even in their absence, perhaps leading to a return to something like the gold standard. In any event, when we go back to the very root of currencies and what makes them valuable, we may well discover a counter-intuitive (at least, to some) truth: that both gold and cryptocurrencies are better placed as stores of value than fiat currencies, such as the pound, dollar or euro.

Sockpuppetry is the new normal. That doesn’t make it healthy

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It’s been nearly three years since Adrian Chen first discussed the Internet Research Agency, a euphemistically titled group which was pumping out pro-Kremlin and anti-American messages for money. At the time, eyes were elsewhere online – it was the year of Ashley Madison, after all, and a time when China ranked alongside Russia (if not higher) in the space of public paranoia.

Even then, the idea of governments astroturfing spaces (i.e. hiring online goons to make it look like their actions had far greater support than in reality) was not new.  China’s 50 Cent Army (a joke on the low rates supposedly paid to the sockpuppets posting pro-Communist Party propaganda) had been floating about since the early noughties. The US had branches for this sort of thing since 2010. The Snowden leaks revealed the UK had been indulging in this sort of thing too.

The recent revelation that astroturing had been used on Reddit and Tumblr thus should have come as a surprise to no-one; that it was the Internet Research Agency involved in it, even less so. It’s tempting, in fact, to say that given that we know how prevalent this practice seems to be, we’re in a better situation than we were in 2015. We have more groups and institutes keen to fact check supposed Russian sockpuppets (more typically called trolls) than ever before. People are, in some ways, more wary than ever of information coming from certain outlets.

In practice, what that means is the disturbing brand of nihilism which once hung out on the corners of 4Chan has become increasingly pervasive. We live in the time of the simulacrum: in which every piece of information is supposedly an illusion, created to hide the lack of any real truth. The videos you watch are going to be created through neural networks, so you can’t believe your eyes; the words you read have already become synonymous with fake news regardless of how you lean politically. To be savvy means to trust nothing, or to go hard in support of institutions which have serious questions about impartiality (Hamilton 68, though a fascinating and at times useful resource, has understandably been accused of being a little too close to the old Cold Warrior mentality of NATO).

The point of sockpuppetry is to inflate the influence of a group, or a country, or an opinion, and to discredit opposing points of view. In some regards, it’s done the latter far more effectively than could have been hoped. Practically any deviation from the norm is now treated as evidence of yet more Russian interference. Sockpuppets, in short, have turned fairly rational and moderate individuals into conspiracy theorists. And conspiracy theorists are, by the nature of society, a joke at best and a concerning fringe at worst.

The age of disbelief is upon us. A little cynicism is healthy; a lot is not. The failures of social media companies to combat this behaviour is a blight which will continue to linger on long after the scandals over Russia have died down.

The Efficacy of Bot Purges

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There’s something rather brutal about the idea of bot purges – perhaps a reflection of the humanity with which we endow human-looking accounts. Twitter’s decision to suspend thousands of accounts last month was less horrific than it sounded: a small attempt to solve a problem which has plagued the platform for over a year now, and has brought into the radar of US and British politicians as an ambivalent if not mercenary hawker of propaganda.

This didn’t stop it from earning the ire of conservative accounts (including some of the more prominent members of the alt-right and related conspiracy theorists), who had found thousands of their followers eviscerated. To them, it represented just another part of the ongoing skirmish with big tech which had attempted to shut them out of the marketplace, or flag their ideas as fake news.

It doesn’t help that at least some of the accounts which Twitter targeted were real conservative commentators rather than strings of code. In fact, it only adds to the ongoing debate about what a bot really is. Granted, there are the most crude examples of accounts which blurt out the same message over and over, but there are plenty of humans who perform similar functions. On the one hand, this arguably says more about the state of Twitter discourse than anything: if your posts look like they’re written by a painfully simple programme, you’re almost certainly not adding a lot to the conversation. The problem only intensifies when we consider that a lot of bot accounts are ‘cyborgs’, partially automated but with a human who can step in as and when necessary.

And then there are sockpuppets – better known as trolls – who voice an opinion for money or patriotism. They’re by no means new or unique to Twitter (Wikipedia has struggled with them for years and years), but at a time when social media has increasingly come under scrutiny, it’s difficult to ignore them. Of course, bot purges can’t capture them: Twitter can only stop automation, not insincere or unethical tweeting.

And therein lies the crux of the problem: purges of bot accounts are like putting a plaster over a serious wound. The people running them will have them back up and running, not least because they’ve proven very quick to adapt to research on automation and integrate it in their strategies. A longer time solution is necessary to restore any meaningful trust in social media. Rather than engaging in heavy-handed crackdowns with little explanation – relying on people not caring enough about what algorithms are really responsible for figuring out who alleged bots are – Twitter could do a lot better with emphasising transparency. Because, at the end of the day, Big Tech has never shown a great concern about its role in affecting democracy, for better or worse: instead, its actions have been dictated by PR concerns.

Moving away from the pedestal of the Philosopher King could do Twitter a little good – and society a whole lot more. Fight bots, by all means, but encourage media education and engage with people too; that’s the way to make the change more than skin-deep.

Does Social Media Really Polarize Our Politics?

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It’s often said that social media has a polarizing effect on our politics. And, on the surface, this narrative makes a lot of sense. The polarization of politics has continued as social media has taken over our brains. And what social media does, among other things, is make a game of earning the approval of your peers, thus solidifying your group identity. When you post something that pleases the sensibilities of your cohort—whether it’s a handsome selfie or a solemn plea for stricter gun control—you get the satisfaction of an immediate bombardment of friendly notifications. The reward structure of the social media experience doesn’t provide incentives for expressing minority views, or objecting to the prevailing narratives, or befriending those who disagree with you.

Moreover, Twitter and Facebook aren’t great places for dialogue. Political arguments are usually futile in real life, even with all of the felicitousness provided by face-to-face interaction. It’s much worse when ideological disagreements need to be reduced to 280 characters, or haveto compete with cute pictures of somebody’s baby. In this setting, sensitivity and nuance doesn’t play well. What gets the most attention is pithiness and aggression. In short, social media enables the self-congratulation and self-separation of mutually hostile political factions. Sounds pretty polarizing, right?

Yes. However, there’s a big and obvious question here, which is whether this is actually any different from the pre-Twitter media landscape. Long before Facebook was ever a gleam in Mark Zuckerberg’s eye, the various political classes selected the media that was most collegial to their respective worldviews. To take America as an example, in previous decades, Christian conservatives tuned into right-wing talk radio to hear about the horrors of the gay agenda, whereas elite liberals picked up Harper’s to read about the horrors of capitalism. (This is still true today, in part.) Bubbles and echo chambers exist in absence of Twitter. All that’s required to create ideological homogeneity is tribal self-selection or homophily—the tendency of people to hang out with people who are like them and agree with them, given freedom of association. That’s definitely a pre-iPhone tendency.

But, of course, it’s still possible that social media has enhanced tribal patterns of behaviour—that this is not a difference of kind, but it is a difference in degree. So, if we check the data, what do we find? Well, it appears that social media does, in fact, have an effect on polarization. It’s just the opposite effect that critics might expect. According to a demographic study by Boxell et al., published by Stanford University, political polarization is actually less pronounced among demographics that use social media more often (young people, essentially). This shows that it’s unlikely that social media is a more powerful driver of polarization than old-fashioned media. (Or it shows that, even if social media does polarize, there’s some countervailing anti-polarizing force that’s much more powerful.)

And, like the just-so story about why social media polarizes, there’s an appealing readymade narrative about why the opposite might be true. While political disagreements on Twitter and Facebook tend to be shallow and nasty, they’re still genuine disagreements—something that doesn’t usually occur in traditional media. The New York Times doesn’t contain a second page declaring that all the articles on the front page are slanted. And while it’s true that debate programs are a staple of political television, such programs are usually staffed by a preexisting team who are paid to perform a predictable set of reactions to ongoing affairs. Meanwhile, on Twitter, it’s quite easy to run into novel objections to everything you believe in, which, even if they aren’t particularly convincing, might compel more considered private reflection.

Or maybe it’s even simpler than that. It’s possible that young people are less polarized because social media is so nasty and tribal. While a minority of social media influencers make a lot of provocative noise, it’s possible that the non-contributing majority is quietly alienated by the vitriol. While a controversial tweet with 1200 retweets looks impressive, there’s no way to measure the number of users who have quietly rolled their eyes and moved on—or have simply quit Twitter altogether.

There’s a larger lesson here, which is that it’s unwise to infer narratives of societal change based simply on the most visible behaviour provoked by one app or another. (Another demonstration of this: millennials have way less sex than their parents, despite the existence of Tinder and all the moral panic surrounding it.) Ultimately, sensationalist narratives about the polarizing effects of social media are just the kind of thing that’s popular on social media.