18 Exponential Changes We Can Expect in the Year Ahead

18 Exponential Changes We Can Expect in the Year Ahead

He is the curator of the weekly newsletter Exponential View, from which the following is adapted. Critics of greater central intervention in our collective affairs will raise the specter of Marx, and often through Friedrich Hayek’s critique of it. Hayek’s notions of the market as the most effective information discovery and transmission mechanism will attract more interest as blockchain-style networks show their utility as resource coordination systems. Aristotle reasserts himself because while we are wealthier than ever before, his call for eudaimonia (human flourishing) will seem to stand above the noise of “recommended for you” consumerism.  Buddha’s relevance will be driven by a greater awareness of mindfulness and contemplation in our dopamine economy. And as machines appear to be more and more lifelike, and neuroscience unravels more mysteries of our consciousness, the quiet contemplation of our subjective personal experience will become a sanctuary for our humanity. Those same nations will curry favor with the platforms to win the putative economic benefits provided by them. These firms will accelerate their efforts to secure platform advantage and raise the baseline from which their settlement will be judged in the years to come.National AI strategies will emerge from more countries. More grounds for cooperation and more reason to argue about intellectual property, privacy, data, and license to operate.Silicon Valley's political culture—and how that has been codified into software, corporate culture, and strategy—will continue to smell. The Valley will hire outsiders to fix these problems or, more likely, just for the optics. They will do so with a narrow, ideological framing that will threaten to hurt us in the coming decades, by which time these networks will mediate many of the resources we need. This matters because information technology systems affect how we build our understanding of the world; they affect how we perceive our set of choices; they affect how we act in that world. In short: they affect our understanding both of the "is" and the "ought." 2. While Silicon Valley leads, both innovation and scaling increasingly occur across the globe. Its focus on AI, supported by the state and its homegrown tech giants, will show up as novel methods and large-scale implementations. The U.S., with its declining health and social outcomes and turn inward, will become less appealing to some entrepreneurs. And its business culture, focusing solely on corporate profits, will lack the motives to innovate in areas that affect the social fabric (for the collective good). Curiously, the European Union will provide room for innovation because of its ability to bring broader groups of stakeholders together than competition alone can foster. We may not see an African firm to rival America’s tech giants anytime soon, but we will see meaningful innovation in fields like ag-tech and distributed power generation. However, the largest firms in the world will hail predominantly from Silicon Valley, and one, most likely Apple, will exceed $1 trillion in market cap this year. These will seek to back emerging winners at a regional and global level (look at Careem and Didi Chuxing in ride sharing, for example). This may create funding gaps at earlier stages in the market, as already evidenced by the seed capital slowdown in Europe and the U.S. One will be voice, both as an input and as the output. The second will be images, where embedded cameras will provide large-scale inputs to machine-learning systems. (One example will be the growth of affective computing applications.)Specialist hardware (think Google’s TPUs and others) and novel frameworks (TensorFlow and its competitors).Cloud-to-edge computing, as we deliver an increasingly large proportion of intelligence at the locality where it is needed.A new paradigm of software development (where the best developers nurture highly parameterized models and cajole the training data to feed them). One group of winners will be the crop of 2013/2014 vintage AI startups now maturing into serious businesses with meaningful revenues and growing fast. Those same firms will move from simple notions of data supply chains to rethink their business model around data network effects and AI lock-in loops. Firms that view AI not as a tool with which to expand their offerings but merely to cut costs will become lords of an ever-diminishing manor. We will see more evidence for the tangible benefits AI tools can give us individually, and we’ll increasingly witness the power of the AI-augmented human. The collective efforts of the research community continue to impress us, especially as we see low-hanging breakthroughs in areas outside of vanilla deep learning, such as reinforcement learning, adversarial networks, one-shot learning, and unsupervised methods. (By the way, we'll be barely any closer to human-like intelligence and no closer to artificial consciousness.) 7. The discussion on how AI will impact employment will shift from solely focusing on the elimination of jobs to how best to help workers accommodate the inevitable change. Those which combine an investment in social goods (like education and a safety net) and maintain a healthy approach to entrepreneurship and innovation will do best. We will also make more progress in understanding questions of trust, fairness, and justice in algorithmic systems. In 2018, the activity in decentralized applications and protocols based on tokenization will increase. Below the speculative froth are sober-minded teams coming together to tackle real problems using the unique attributes of blockchain technologies. These areas include how to build a data commons to incentivize the sharing of data, allow the sharing of models, and using blockchains and smart contracts for individual AIs to mediate their machine-to-machine interactions. 9. Sordid revelations in crypto-speculation will be outweighed by the wall of money entering the assets class. Asinine press releases, speculative investors, and shady enablers get out into the market much faster than the technology can become useful. This lurid funk will obscure technology progress as more out-and-out frauds are met with regulatory intervention and commentators watch speculators from the safety of their schadenfreude pulpits. This will see an increasing range of products for institutional investors and, crucially, high-net-worth investors wanting to get exposure to this asset class. 10. KITT, the car from Knight Rider, will remain the gold standard for autonomous vehicles. Autonomous vehicle pilots will become increasingly ambitious, but the real-world hurdles will still take time to navigate, even with friendly city regulators. Separately, the success of applying deep-learning techniques to electronic health records, low-quality consumer tracking data, and medical images will create confidence in producing breakthrough applications. Aging populations, coupled with an affordability crunch at both the state and private level, will increase the need for novel solutions—which AI-powered digital health might just provide. 13. The U.S. midterm elections will be a focus of systematic information warfare, with the advantage with the perpetrators. As Bill Gates said, "Most people overestimate what they can do in one year and underestimate what they can do in 10 years." Likewise, most annual predictions overestimate what can occur in a year, and underestimate the power of the trend over time.  Here are 18 areas which I think will be interesting to watch in the coming year: 1. International relations, the political economy, and governance will desperately need new design patterns as we enter a new phase of the digital revolution. The main political parties standing for election (and many groups who are not) use a wide spectrum of tools to target, persuade, and mislead voters, such as never before. Recommended for You True believers in AR and mixed reality will persevere, but the opportunity for large-scale change afforded by AI and blockchain—especially in fintech, health care, and energy—will attract the majority of driven entrepreneurs. Smart firms will start to build up their capabilities in this domain today to reap rewards in the future. The enhanced privacy features in iOS and Google Chrome, and the requirements of data obligations of the EU’s General Data Protection Regulation will hurt ad tech and programmatic advertising. Facebook and Google will barely notice and will continue to dominate the market. The price of renewables will continue to decline and new solar and wind contracts will be substantially below the best fossil fuels can offer. On the downside, the energy consumption of mining Bitcoin and other tokens will continue to grow at more than 20 percent per month, unless there is a huge price correction. Consumers will increasingly make purchase and investment decisions based on their resonance with the ethical positioning of a firm. These will get amplified by industry—particularly the insurance industry, which needs to price in risks related to climate change or regulatory malfeasance. Marx because the last 50-year consensus between workers and employers and financial capital is strained, so some will look for the pendulum to swing back. Others will look at the combination of increasingly cheap energy (reducing the cost of production toward nil) and increasingly capable machines (reducing the average human’s ability to be paid for their outputs) and argue only a state of radical abundance—or “each according to their needs”—can work.

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The future of FinTech is racist, according to this anonymous data scientist

The future of FinTech is racist, according to this anonymous data scientist

This is an excerpt from a long interview between an anonymous data scientist and Logic Magazine about AI, deep learning, FinTech, and the future, conducted in November 2016. I talked to a guy who used to work for one of these companies. Not one of the ones I mentioned, a different one. And one of their shticks was, “Oh, we’re going to use social media data to figure out if you’re a great credit risk or not.” And people are like, “Oh, are they going to look at my Facebook posts to see whether I’ve been drinking out late on a Saturday night? It’s because, with your social media profile, they know your name, they know the name of your friends, and they can tell if you’re black or not. They can tell how wealthy you are, they can tell if you’re a credit risk. And my consistent point of view is that any of these companies should be presumed to be incredibly racist unless presenting you with mountains of evidence otherwise. I was actually floored, during the last Super Bowl I saw this SoFi ad that said, “We discriminate.” I was just sitting there watching this game like I cannot believe it — it’s either they don’t know, which is terrifying, or they know and they don’t give a shit, which is also terrifying. I don’t know how that court case is going to work out, but I can tell you in the next ten years, there’s going to be a court case about it. And I would not be surprised if SoFi lost for discrimination. And in general, I think it’s going to be an increasingly important question about the way that we handle protected classes generally, and maybe race specifically, in data science models of this type. Can you use things that correlate with the racial demographics of their zip code? And we know what we’re doing for mortgage lending — and the answer there is, frankly, as a data scientist, a little bit offensive — which is that we don’t give a shit where your house is. We just lend. It’s a fucking app, and you’re like, “How can I get a million dollar loan with an app?” And the answer is that they legally can’t tell where your house is. And the algorithm that you use to do mortgages has to be vetted by a federal agency. That’s an extreme, but that might be the extreme we go down, where every single time anybody gets assessed for anything, the actual algorithm and the inputs are assessed by a federal regulator. I actually view it a lot like the debates around divestment. You can say, “Okay, we don’t want to invest in any oil companies,” but then do you want to invest in things that are positively correlated with oil companies, like oilfield services companies? I think it’s the same thing where it’s like, okay, you can’t look at race, but can you look at correlates of race? I’m reminded a bit of Cathy O’Neil’s new book, Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy (2016). It’s AI only in the loosest sense of the word. One of her arguments, which it seems like you’re echoing, is that the popular perception is that algorithms provide a more objective, more complete view of reality, but that they often just reinforce existing inequities. And the part that I find offensive as a mathematician is the idea that somehow the machines are doing something wrong. We as a society have not chosen to optimize for the thing that we’re telling the machine to optimize for. It’s just that they’re literally amoral, and if we told them the things that are okay to optimize against, they would optimize against those instead. It’s a frightening, almost Black Mirror-esque view of reality that comes from the machines, because a lot of them are completely stripped of — not to sound too Trumpian — liberal pieties. You can load in tons and tons of demographic data, and it’s disturbing when you see percent black in a zip code and percent Hispanic in a zip code be more important than borrower debt-to-income ratio when you run a credit model. When you see something like that, you’re like, “Ooh, that’s not good.” Because the frightening thing is that even if you remove those specific variables, if the signal is there, you’re going to find correlates with it all the time, and you either need to have a regulator that says, “You can use these variables, you can’t use these variables,” or, I don’t know, we need to change the law. As a data scientist, I would prefer if that did not come out in the data. I think it’s a question of how we deal with it. But I feel sensitive toward the machines, because we’re telling them to optimize, and that’s what they’re coming up with. I can tell you that a lot of the opportunity those FinTech companies are finding is derived from that kind of discrimination because if you are a large enough lender, you are going to be very highly vetted, and if you’re a very small lender you’re not. And it’s a reasonable formula, it’s not a magic formula, but they’re not quantitatively assessing markets and trying to make predictions. They probably did not set up their business to be super racist, but I guarantee you they are super racist in the way they’re making loans, in the way they’re making lending decisions. You could say, “They’re a company, they’re providing a service for people, people want it, that’s good.” But at the same time, we have such a shitty legacy of racist lending in this country. They’re applying a formula about whatever stock and bond allocations to make — it’s not a bad service, but it’s super hyped. I just think that there is going to be a court case in the next ten years, and whatever the result is, it’s going to be interesting. Logic is a magazine about technology that comes out three times a year. There’s a function that’s being optimized — which is, at some level, what a neural net is doing. I actually think this is going to be a huge point of contention moving forward.

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Blockchain’s Applications Extend Beyond FinTech and Cryptocurrencies

Blockchain’s Applications Extend Beyond FinTech and Cryptocurrencies

A cursory online search and you will find many opposing viewpoints on the value of cryptocurrency—whether it’s a bubble, say, or if it’s the future of money. If you work in the medical profession—or have had to deal with transferring prescriptions, medical information, or anything else between clinics and doctors—you will know it can sometimes be difficult to reconcile records. For example, every time a patient checks in to see a healthcare provider, their visit could be recorded and added to the healthcare blockchain. An API used to update this blockchain could give permissions to different organizations on how much information people or institutions could see about each block. Changes to each visit record could also be closely monitored and reviewed, and new information could be appended to the patient’s block. However, all this hype around cryptocurrency has caused a lot of people to look past the actual underlying technology: the blockchain. Essentially, a medical care blockchain system could provide solutions to some of the most difficult challenges facing medical record keeping: privacy, consistency, and accuracy. Healthcare blockchain infographic courtesy of Deloitte.Blockchain in Supply Chain ManagementBecause blockchain is so useful for record keeping, it isn’t surprising that it can also be a powerful tool for supply chain management. In the pilot, they tracked the movement of food from the farm to the packaging plant, through shipping, onto the shelf, and then eventually to the consumer. The information that can be acquired along the way includes the origin of the food, how it was processed, how it was shipped, and how long it’s been on the shelf for. In the event that there was information indicating some food might not be safe, it would be easy to identify exactly which food items were impacted and track where it had been delivered. It would also make it easier to identify what went wrong in the supply chain to make the food unsafe in the first place. Blockchain technology has a variety of applications beyond just cryptocurrency; it can be used in healthcare, supply chain management, and even cloud storage. This could speed up access and remove reliance on being able to connect to one single centralized entity.  As you can see, there are many ways that blockchain technology can be used. Even if you don’t believe in the cryptocurrency craze, there are still important features in the underlying blockchain technology that could impact many industries. Any industry that processes data, especially sensitive information that could require security, could see blockchain implemented in the near future. Whether you think Bitcoin is an investment bubble that’s about to burst or if you believe cryptocurrencies are the future of finance, likely blockchain will continue to evolve into a technology we’ll all use in some form or another in the future. Let's take a look at how blockchain technology could affect you in the not-too-distant future, even if you're not investing in cryptocurrencies.What Is Blockchain?Blockchain is a decentralized “ledger” technology—in extremely basic terms, a blockchain is a record of transactions. Every time a transaction occurs, the network will either "agree" or "disagree" with it. If more than 51% of the network agrees the transaction has happened, then that transaction is permanently added to the blockchain and all nodes in the network will update to reflect that.

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2017 in review: Dirty politics trumped development economics this year

While most of the economic focus is on our twin deficits, a major challenge that is bubbling under is water stress. According to WaterAid, “Pakistan is among the world’s 36 most water-stressed countries” and “among the top 10 countries with the greatest number of people living without access to safe water.” As per the Pakistan Council of Research in Water Resources, Pakistan may run dry by 2025 if the present conditions continue. In another report by Institute of Public Policy, there are five challenges on the supply side: water scarcity resulting from higher demand and diminishing capacity of reservoirs, excessive conveyance losses, deteriorating infrastructure, high operation costs and an excessive groundwater use. ATM skimming hit the headlines towards the end of the year. The scandal was far from huge.We are talking about less than 1,000 people and just about Rs1 crore in the whole country. On the bright side, the media outcry created more awareness about cyber crime than the National Response Centre for Cyber Crime under the FIA could ever expect to achieve through its awareness activities. The Economic Survey put the GDP growth for 2016-17 at 5.3pc, noting that it is the “highest growth rate recorded in a decade.” The World Bank in its Pakistan Development Update said: “Pakistan's economic performance remained robust during the fiscal year 2017 (FY17) as growth continued to accelerate.”IMF’s Article IV Consultation had a similar view: “Pakistan’s outlook for economic growth is favourable, with real GDP estimated at 5.3pc in FY 2016/17 and strengthening to 6pc.” The State Bank of Pakistan’s (SBP) State of the Economy also agreed: “The real GDP growth in FY17 was the highest during the last ten years. It was very much the making of powerful Pakistanis eager to play a game of thrones. They put their ambition, their ego, and the glory of their institution above that of Pakistan. Be it any party or the parliament, the judiciary, the army, or the media, all have suffered reputational damage during 2017. This is according to the Consumer Price Index by Pakistan Bureau of Statistics (PBS), if you are willing to believe the Bureau. That surely does not mean that the price level of essential goods is within the reach of common Pakistanis. Inflation was contained thanks to factors like lower international petroleum prices, which have begun to rise, and a stable Pakistani rupee, which has started to weaken. This is the provisional result of the 2017 census data by the PBS. Economy was growing, inflation was low, the rupee was stable, CPEC was progressing, Pakistan’s credit rating had improved, and the stock market was racing. The compound annual growth rate for the population since 1998 turns out to be 2.4pc, well above the global average. The share of population of Punjab and Sindh decreased while that of Khyber Pakhtunkhwa and Balochistan has increased. According to the Word Bank, Pakistan is the sixth most populous country following China, India, USA, Indonesia and Brazil. According to the monetary policy statement issued in November, “The already buoyant growth in fixed investment gained further traction at a slightly higher level relative to FY17, while both working capital loans and consumer financing showed encouraging trends.” SBP says that the prospects of achieving the 6pc target of real GDP growth continue to be strong due to the availability of cheaper money and higher credit off-take by the private sector. Another statistic that is close to the hearts and minds of Pakistanis is the unemployment rate. Officially, it is around 6pc but not everyone is willing to believe it. The credibility of economic data in Pakistan in general has long been subject to debate. But the unemployment number stands out because of the incredulity surrounding it. The army of applicants applying for every advertised job in 2017 surely does not suggest unemployment is low. In one of its report, marketing research firm Nielsen puts the employment rate at 51pc, leaving the unemployment rate much higher. Economic issues took a back seat for most of the year as the leadership got occupied with the ongoing political turmoil. The government was greatly weakened and its fragile writ was fully exposed in the Islamabad sit-in. Following the disqualification and resignation of prime minister Nawaz Sharif, the embattled finance minister Ishaq Dar has taken leave of absence. A new governor assumed office at SBP, and an acting chairman was appointed at Securities and Exchange Commission Pakistan (SECP) after the former chairman was suspended in the “record tampering” case. It has been a surreal experience watching all the key policy makers get replaced in a matter of months. The economic challenges were mounting, the economic leadership was conspicuous by its absence, and no one was counting the cost of political uncertainty. The seventh round of the CPEC Joint Cooperation Council took place in Islamabad in November. According to the official announcements regarding the long-term plan, “By 2025, the CPEC building shall be basically done, the industrial system approximately complete, major economic functions brought into play in a holistic way, the people’s livelihood along the CPEC significantly improved, regional development more balanced and all the goals of Vision 2025 achieved.” The largest sector under CPEC is energy, where shortages have long been the bane of our economy. The government is now examining a proposal to replace the US dollar with the Chinese yuan for trade between China and Pakistan. Unsurprisingly, of the total global remittances, 80pc are received by 23 countries, led by China, India, the Philippines, Mexico and Pakistan. The World Bank’s Migration and Development Brief says that Pakistan had witnessed 12pc growth in remittances in 2015, which moderated to about 2.8pc in 2016 and is expected to grow by a meagre 1.4pc in 2017. Remittances during July to October 2017 have reportedly grown by 2.3pc and it is an open debate if the growth has slowed down as much as anticipated. Unlike some of the traditional economic indicators, such as inflation and unemployment, terror and political violence are not systematically measured and publicised in Pakistan. A report published in 2017 by the US State Department says that terror in Pakistan is on the decline. The violent ending of the Islamabad sit-in by a faction of the religious right shows that political violence is very much alive and it is hurting economic activity. The chaos gained momentum with the formation of the Panama case JIT in April and then culminated with the Islamabad sit-in by a faction of the religious right in November. The tax rate on capital gains on securities was increased to a flat 15pc for filers and 20pc for non-filers regardless of holding period.A super tax of 4pc for banking companies and 3pc for persons other than banking companies earning more than Rs500 million was extended to 2017-18. How the Federal Board Revenue has gone about increasing tax revenue has been criticised and the Board continues to be assailed for corruption. If critics are to be believed, the government is now set to miss all the major budget targets including the GDP growth of 6pc, containing budget deficit of 4.1pc, and increasing tax- -to-GDP ratio of 13.7pc. Pakistan’s stock market soared because large inflows by foreign funds were expected after the country regained entry into the MSCI Emerging Market Index. Together with mounting political uncertainty, rising deficits, disappointing budget, and fears of depreciation of the Rupee, the MSCI surprise was a hard blow for the investors. After rising 46pc in 2016, the KSE-100 index has fallen by more than 25pc from the all-time high it hit in 2017. On the bright side, in a welcome break from the past, and despite the very large movements in the market, there have been no chain defaults. In a leap forward for PSX, its stock brokers sold 40pc of their shares for US $85 million to a consortium of Chinese securities exchanges, Pak-China Investment Company, and Habib Bank Limited. Following the strategic investment, PSX also got listed on itself though there was limited investor interest in its shares during the book building process. Many investors in Pakistan are still trying to get their head around the fact that the exchange itself has become a listed company. HBL, one of the largest banks in Pakistan, was rocked by a money laundering scandal that shook the entire banking sector. It is a huge amount, but still less than half the $630 million that the US authorities had reportedly assessed. A feather in SECP’s cap, this is the longest piece of legislation ever approved by Pakistan’s parliament.This was a mega project many years in the making. This act will continue to touch each of the roughly 80,000 companies registered in Pakistan and the lives of millions of Pakistanis for many years to come. As one news report in September put it, fiscal deficit hit 5.8pc of GDP reaching “Rs1.864 trillion mark in absolute terms, the highest in four years of the PML-N government as well as in the country’s 70-year history.” IMF says Pakistan has the potential to reach a tax-to-GDP ratio of 22pc but it remains just that: unrealised potential. New records of trade deficit were being set with such frequency that it became difficult to keep up. “Never before in the country’s history have imports been over two-and-a-half times of exports as they are now,” lamented an observer, as trade balance worsened. The ratio of gross public debt to GDP, as reported by the SBP, remained above 60pc. There has been ongoing speculation as to whether Pakistan would return to borrowing from IMF and face the painful adjustments. The oversubscription and competitive yields of the issues show the creditors of Pakistan are less concerned about our economic challenges than some of the local economists. But early in December, “the State Bank launched what appeared to the rest of us like an ambush” and the rupee, that opened at 105.5 against the dollar, quickly hit 109.5, and has remained volatile since.

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Computer programs deciding how long people spend in jail

Computer programs deciding how long people spend in jail

Israni notes that while judges and juries are notoriously prone to human failures in reason, it remains true that a “computer cannot look a defendant in the eye, account for a troubled childhood or disability, and recommend a rehabilitative sentence.” The alternative is true as well. Computers can miss red flags, while traits that look good on paper can outweigh more serious issues, favorably skewing a defendant’s score.“A guy who has molested a small child every day for a year could still come out as a low risk because he probably has a job,” Mark Boessenecker, a Superior Court judge in California’s Napa County, told ProPublica. “Meanwhile, a drunk guy will look high risk because he’s homeless. These risk factors don’t tell you whether the guy ought to go to prison or not; the risk factors tell you more about what the probation conditions ought to be.”At the end of the day, the ProPublica investigation found that COMPAS in particular, and risk assessment programs in general, are not very good at their jobs.Only 20 percent of the people predicted to commit violent crimes actually went on to do so. When a full range of crimes were taken into account — including misdemeanors such as driving with an expired license — the algorithm was somewhat more accurate than a coin flip. In doing so, the court essentially (though not explicitly) gave its blessing to the program’s use.In an era in which the Trump Department of Justice has repeatedly promised to push policies that make the justice system fail at even more turns, the use of AI programs in our courts is all the more dangerous. At the very least, courts—which don’t understand how the programs they use make the assessments they consider—should attempt to find more transparent systems and to mandate oversight that makes those systems function at optimal level. But that would actually be a departure from the way the courts have always functioned in this country, and it would require the U.S. to develop a real commitment to justice. Essentially a digital questionnaire, COMPAS poses 137 queries, then uses the answers to determine, on a scale from 1 to 10, whether a defendant is at a high or low risk of committing more crimes. (No one, save for the manufacturer, knows precisely how COMPAS’ proprietary algorithm works, and Northpointe has repeatedly declined to offer greater transparency.)Risk scores are supposed to be just one of a constellation of factors that inform sentencing decisions, but research has found those numbers often weigh heavily on sentencing decisions. A 2016 ProPublica study found that COMPAS is “particularly likely to falsely flag black defendants as future criminals, wrongly labeling them this way at almost twice the rate as white defendants.” The analysis also determined that white offenders were wrongly given particularly low scores that were poor predictors of their real rates of recidivism. Ellora Thadaney Israni, a former software engineer and current Harvard Law student, notes that without constant corrective upkeep to make AI programs like COMPAS unlearn their bigotry, those biases tend to be further compounded. “The computer isworse than the human,” Israni writes at the New York Times. “It is not simply parroting back to us our own biases, it is exacerbating them.”Beyond helping an already racist system perpetuate justice inequalities, by reducing a defendant to a series of facts and data points without nuance or human understanding, risk assessments miss mitigating factors that offer a fuller picture.

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Flashback 2017: Health-tech startups ride AI wave; e-pharmacies lead fundraising

Flashback 2017: Health-tech startups ride AI wave; e-pharmacies lead fundraising

Funding into the health-tech sector stabilised in 2017 from the over-exuberance seen in 2015 and slowdown witnessed in 2016. In 2016, online pharmacies came under the scanner of the Indian drug regulator. The Drug Controller General of India had issued a circular in January last year stating that sale of drugs over the Internet goes against the provisions of Drugs and Cosmetics Rules, 1945. It highlighted the need frame laws to regulate the nascent online pharmacy industry in the country. Another key highlight of the year is the role of artificial intelligence in healthcare, with a number of AI-powered health-tech startups raising funds. In a an interaction with VCCircle in August this year, Prashant Tandon, founder of online pharmacy 1mg said that the regulations governing these firms fall under multiple ministries and hence clarity is of utmost importance. “We are governed by the IT Act for marketplaces, the Drugs and Cosmetics Act for pharmacy operations, and others. We are asking for clarity so that the drug inspector doesn’t get to say that he is concerned with only one part of the law. Most of the issues crop up because the local level government does not have much time to figure out all the Acts,” he explained. He also wants the law to be uniformly applied to both online and offline players and has called for a central registry of e-pharmacies operating in India, in order to differentiate the illegal players from the legal ones. Besides e-pharmacies, healthcare startups employing AI also attracted investor attention, including medical-technology startup SigTuple, which raised $5.8 million (around Rs 38.8 crore) in February 2017 in a Series A round led by Accel Partners. Nirmai, which stands for non-invasive risk assessment with machine learning, uses big data analytics and artificial intelligence over thermal images for the early detection of breast cancer. Investor sentiment into health-tech picked up in 2017, which saw inflows worth $162 million being made into the sector versus $84 million in 2016, provisional data from VCCEdge, the research platform of News Corp VCCircle, shows. Users can also discuss their symptoms with a chatbot and can also consult with doctors and hospitals listed on the platform. Though the healthcare sector shows a lot of promise with tech-oriented solutions already being implemented, there are still many issues that need to be addressed, say investors. India needs more physical infrastructure like labs and hospitals and the country also suffers from a huge shortage of doctors and diagnostic technicians, said Mohan Kumar, executive director at Norwest Venture Partners. “You only need to apply the knowledge and the adoption is much easier in healthcare. Considering the scale of requirement, this is still an under-penetrated area and the technology used is old, and the upgradation is easier to do,” he explained. In contrast, investor interest peaked in 2015 with $259 million being poured into the sector, while in 2014, $122 million investments were made, the data revealed. Healthcare in the west has been undergoing digitisation for years, while in India, it was initiated mostly by startups. The adoption of insurance and awareness for prevention is also higher, so the business is tougher in India but the opportunities are in the country as more, Anoop Polavaram, operating partner with Aspada Investment Advisors, explained. He adds that India is years behind in medical products and devices and startups should focus on these sectors to make a meaningful impact. Leave Your Comment Debjyoti Roy and Joseph Rai 8 months ago Bengaluru-based artificial intelligence (AI) startup Niki.ai has raised fresh… Vijayakumar Pitchiah 3 days ago Institutional investors exercised considerable restraint in the calendar year… Vijayakumar Pitchiah 4 days ago Despite investors remaining cautious throughout 2017, the hectic activity around… Digital healthcare platform Practo received the bulk of the investment this year. The company is looking to sell medical insurance and medical devices on its platform as it looks for avenues for monetisation apart from its medical records platform for doctors.

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After cashing in on note ban, fintech firms all wired-up for consolidation

After cashing in on note ban, fintech firms all wired-up for consolidation

Industry experts are of the view that the space is waiting to witness a massive consolidation, since the technology in the financial segment is changing rapidly, making many solutions redundant and obsolete. For example, while demonetisation led to adoption of PoS (Point of Sale) terminals, technology such as UPI payments and QR Code are set to become a major threat to the PoS machine in the coming year. Mergers down the lineWhile 2017 has been a crucial year in the fintech space, 2018 will be the year of collaboration and consolidation of two, or even more, platforms, leveraging their respective expertise to offer a more robust solution, said Ravi Goyal, Founder and MD, AGS Transact Technologies, a provider of end-to-end payment solutions. Manish Lunia, co-founder of Flexiloans.com, a start-up offering micro credits to small businesses, said: “Consolidation in lending will be a ‘high probable event’ in the coming year with players trying to find the right niche, expand target segments and growth verticals, and with banks increasingly wanting to digitise lending verticals.” Besides, the segment will witness transformational opportunities in the coming year due to GST data availability, Electronic-National Automated Clearing House (e-NACH) mandates and PoS digitisation initiatives of the government, that will expand the eligible borrower ecosystem, Lunia added. Bhupinder Singh, founder and CEO of credit-lending platform InCred, said that as more people become part of a verifiable database through Aadhaar, and gain comfort in transacting digitally, many of the current roadblocks will be removed. Finding loyalsIn 2018, the focus of most players will be to provide hassle-free experience and garner a loyal customer base, he added. Fintech companies and new-age NBFCs have already begun optimising the delivery of customer experience by leveraging technology such as cutting-edge algorithms and data science to provide financial services in a flexible and convenient manner, which is going to improve further. “We also see incumbent players collaborating with fintech companies in the areas of underwriting, technology and analytics, to bring bespoke product offerings and superior customer experience to the market. Rohit Lohia, COO and co-founder of online lending platform CoinTribe, said: “While in the payments space, the winners have been clearly marked out, on the lending side, the rapidly mushrooming number of fintech start-ups will continue to create an indecision among investors on who to back.” This will lead to a lot shake-up of ‘me-too’ models that have jumped in to cash in on increasing investor interest. Experts say P2P is unlikely to grow big, constrained by the regulatory limits on investments through the platforms, effectively ruling out HNIs.The new year might also see regulatory activity around co-lending and securitisation market, facilitated by lending marketplaces.While payments and lending will continue to get the most attention in the fintech space, 2018 might also see some players break out in the AI, blockchain and robo-advisory space. The year witnessed some of the biggest reforms and innovations in the digital payments space, starting from UPI (Unified Payments Interface), audio QRs and to P2P payments to payments banks. The segment, termed the most disruptive and agile among the tech-driven sectors, also got some major boost this year with the government announcing new initiatives and reforms such as demonetisation and the Goods and Services Tax. The year witnessed some of the biggest reforms and innovations in the digital payments space, starting from UPI (Unified Payments Interface), audio QRs and to P2P payments to payments banks. Investments galoreBesides support from the government, the segment also got the maximum amount of funding, helping create awareness among people. Too many cooks?However, experts are of the view that while fintech brought the most innovative solutions and disruption into the financial services sector with players using artificial intelligence, data analytics, blockchain and machine learning, to lure more customers, the segment has lately become overcrowded with too many players trying to target the same set of consumers. Industry experts are of the view that the space is waiting to witness a massive consolidation, since the technology in the financial segment is changing rapidly, making many solutions redundant and obsolete. For example, while demonetisation led to adoption of PoS (Point of Sale) terminals, technology such as UPI payments and QR Code are set to become a major threat to the PoS machine in the coming year. Mergers down the lineWhile 2017 has been a crucial year in the fintech space, 2018 will be the year of collaboration and consolidation of two, or even more, platforms, leveraging their respective expertise to offer a more robust solution, said Ravi Goyal, Founder and MD, AGS Transact Technologies, a provider of end-to-end payment solutions. Manish Lunia, co-founder of Flexiloans.com, a start-up offering micro credits to small businesses, said: “Consolidation in lending will be a ‘high probable event’ in the coming year with players trying to find the right niche, expand target segments and growth verticals, and with banks increasingly wanting to digitise lending verticals.” Besides, the segment will witness transformational opportunities in the coming year due to GST data availability, Electronic-National Automated Clearing House (e-NACH) mandates and PoS digitisation initiatives of the government, that will expand the eligible borrower ecosystem, Lunia added. Bhupinder Singh, founder and CEO of credit-lending platform InCred, said that as more people become part of a verifiable database through Aadhaar, and gain comfort in transacting digitally, many of the current roadblocks will be removed. The segment, termed the most disruptive and agile among the tech-driven sectors, also got some major boost this year with the government announcing new initiatives and reforms such as demonetisation and the Goods and Services Tax. Fintech companies and new-age NBFCs have already begun optimising the delivery of customer experience by leveraging technology such as cutting-edge algorithms and data science to provide financial services in a flexible and convenient manner, which is going to improve further. “We also see incumbent players collaborating with fintech companies in the areas of underwriting, technology and analytics, to bring bespoke product offerings and superior customer experience to the market. Rohit Lohia, COO and co-founder of online lending platform CoinTribe, said: “While in the payments space, the winners have been clearly marked out, on the lending side, the rapidly mushrooming number of fintech start-ups will continue to create an indecision among investors on who to back.” This will lead to a lot shake-up of ‘me-too’ models that have jumped in to cash in on increasing investor interest. Experts say P2P is unlikely to grow big, constrained by the regulatory limits on investments through the platforms, effectively ruling out HNIs.The new year might also see regulatory activity around co-lending and securitisation market, facilitated by lending marketplaces.While payments and lending will continue to get the most attention in the fintech space, 2018 might also see some players break out in the AI, blockchain and robo-advisory space. Investments galoreBesides support from the government, the segment also got the maximum amount of funding, helping create awareness among people. Too many cooks?However, experts are of the view that while fintech brought the most innovative solutions and disruption into the financial services sector with players using artificial intelligence, data analytics, blockchain and machine learning, to lure more customers, the segment has lately become overcrowded with too many players trying to target the same set of consumers.

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The 7 Key FinTech Trends To Watch Out For In 2018

The 7 Key FinTech Trends To Watch Out For In 2018

EY’s Fintech Adoption Index (2017), a survey of more than 22,000 digitally active consumers, ranks India second (52%) behind China (69%) in terms of percentage of the digitally active population. Digital payments reached 1,162 crore transactions between April and November and are expected to exceed 1,800 crore in the current fiscal. Beyond payments, interest in fintech startups in areas like blockchain, artificial intelligence and lending are just some of the focus areas that will garner attention. This integration combines the strengths of both – the administration of fintech with the strength and reach of traditional banking. The rise in digital payments and online lending also makes the sector exposed to hackers who are always on the prowl to feed on vulnerable security. Hence, the sector is always innovating to ensure the security of sensitive customer data and information. Coupled with cheaper mobile data rates and the technological ease of digital payments, these numbers boil largely down to the initiatives by the government to boost financial inclusion and promote a cashless society. As most cybersecurity measures up till now have been reactive rather than preventive in nature, banks will now begin to adopt additional measures to ensure data security at all stages using a combination of encryption, OTPs, biometric authentication and more. P2P Moneylending Motivated by the intention of democratising financial services while aiming for exponential growth, these FinTech startups will come up with newer models for lending, especially in the P2P Lending space. Several major banks in India such as HDFC, ICICI, and YES Bank adopted chatbots for seamless customer interactions and query-solving in the year gone by. In 2018, we can expect more chatbots to be deployed with improved quality of interactions, the speed of responses and accuracy in decision-making. Consumers are now increasingly open to incorporating technological innovations in their daily lives, mobile data is getting cheaper, government regulations are leading the charge and private players are making major investments. Keeping in mind the pace with which India’s payment landscape is developing, it won’t come as a surprise if India overtakes China in the not-so distant future. This story is a part of our Predictions series where we bring to you the forecasts and predictions for the year 2018, hand-curated by the Inc42 editorial team and industry experts. Note: The views and opinions expressed are solely those of the author and does not necessarily reflect the views held by Inc42, its creators or employees. Inc42 is not responsible for the accuracy of any of the information supplied by guest bloggers. 2017 has been the year which saw e-wallets and digital payments come to the fore, placating the masses post demonetization. Come 2018, this trend will likely mature as more and more Indians turn to the digital side of things; becoming the payment mode of choice for a lot more users. The Government will continue to push digitisation of financial systems and the consumer will, more and more, be encouraged to shift to digital platforms for financial transactions.

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It Was a Big Year for AI – Slate Magazine (blog)

It Was a Big Year for AI – Slate Magazine (blog)

Successful astronomical discoveries often center around studying data—lots and lots of data—and that is something A.I. and machine learning are exceedingly good at handling. In fact, astronomers used artificial intelligence to sift through years of data obtained by the Kepler telescope to identify a distant eight-planet solar system earlier this month. From 2009 to 2013, the Kepler telescope’s photometer snapped 10 pixel images of 200,000 different stars every half hour in search of changes in star brightness. If a star dimmed and brightened in a regular, repeating pattern, that could be an indication that it has planets orbiting. (You can also use that information to estimate the size and length of orbit of a planet circling a particular star.) University of Texas at Austin astronomer Andrew Vanderburg and Google software engineer Christopher Shallue developed the neural network that made the discovery using 15,000 known exoplanet indicators. The planet the duo discovered, dubbed Kepler-90i, appears to be the third planet orbiting its star, much like our own Earth. Google’s DeepMind researchers developed an A.I. that plays the ancient, complex Chinese strategy game of Go. The initial version defeated the world’s best Go player in May, but that wasn’t enough. While A.I. and data-focused machine learning have been around for decades, the algorithmic technologies have made their presence known in a variety of industries and contexts this year. An A.I. developed by Carnegie Mellon’s computer science department recently beat professionals at one of the most difficult styles of poker, no-limit Texas Hold’em. In a 20-day competition with a $200,000 prize pool and 120,000 total poker hands played, Carnegie Mellon’s A.I., Libratus, beat the world’s top poker professionals. Microsoft UK’s chief envisioning officer Dave Coplin has called A.I. “the most important technology that anybody on the planet is working on today,” and Silicon Valley companies seem to have taken that to heart: They’ve been hiring A.I. experts right and left, and with those in short supply, they’ve started teaching employees the fundamentals of A.I. themselves. We exaggerate: Several different artificial intelligence programs (including ones developed by Google, Microsoft, and Facebook) learned how to write basic code at a level that could help non-programmers with complicated spreadsheet calculations or reduce some of the tedium that experienced developers have to deal with. This A.I. can understand a mathematical problem you need to solve, look through existing examples of code for similar problems, and then develop a code-based solution. DeepCoder could eventually be useful for those who can’t or don’t want to learn to code but need to use a code-based solution for computations (for example, tricky spreadsheet calculations). The solutions are relatively simple and, in terms of solution and structure, are based on situations the A.I. has experienced before. Google’s program, in contrast, taught itself to program machine learning software and, in one case, learned to recognize objects in photos—a much more challenging task. Named AutoML, the program ended up achieving a 43 percent success rate at its task—4 percentage points better than the code developed by its human peers. AutoML’s biggest benefit, though, is in automating the process of developing machine learning models, a process that’s normally time consuming for human machine learning experts. The two A.I. agents, Bob and Alice, started out speaking in English but then…developed their own language to speak in. “Agents will drift off understandable language and invent codewords for themselves,” said Dhruv Batra, visiting research scientist from Georgia Tech at Facebook A.I. While this got a lot of blowback in the press (“creepy” was a common headline descriptor), it’s actually a fairly common occurrence. A.I. systems evolve using a rewards-based system, and if there’s no benefit from a particular course of action, they’ll try something else instead. Still, the Facebook researchers eventually shut down the A.I. bots since their goal was to create entities that will eventually interact with people—there was no Her-style ending for these digital acquaintances. And earlier this year, Facebook came under fire for the algorithmically generated categories advertisers could use to target users, which included hateful groups and topics such as “Jew hater.” Situations like these have prompted experts to urge companies and developers to be more transparent about how their A.I. systems work. However, in many other cases—especially of late—A.I. has been used to good end: To make discoveries, to better itself, and to help us expand beyond the limits of our human brains.

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