Equifax Deserves the Corporate Death Penalty

21

October

2017

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“Equifax Deserves the Corporate Death Penalty”, one of yesterday’s headlines on WIRED read (Fein, 2017). Equifax is one of the States’ three big credit reporting companies that keep financial data on everyone, so that for example landlords can determine whether or not someone is trustworthy. They suffered a severe security breach, lasting from mid-May through July, but only notified the public in early September.

Equifax failed to protect sensitive personal information of 145 million Americans, nearly half the country’s population. The information in question pertains to names, birth dates, addresses, driver’s license and even worse, social security numbers. As these things cannot be changed as easily as a phone number, this may make a lot of people vulnerable to identity theft. Even more outrageous, to protect themselves, they have to pay credit freeze fees – totalling $4.1 billion – to Equifax (Feng, 2017). Additionally, the identity protection program Equifax is offering for free to anyone who wants to enrol, has two problems: the checker that’s supposed to let you know that you might’ve been hacked is broken; and enrolling in the program prevents the participant in suing Equifax (Profis, 2017).

Breaches of more sensitive data, like bank, social-security, address, and health or employment records, have become so common, a lot of people just shrug an sigh, as an article in The Atlantic puts it (Bogost, 2017). Through the demand of consumers and the willingness of corporates, software development has become easy and popular, making security an afterthought instead of the top priority it should be. Are we becoming indifferent to privacy breaches, just when cybersecurity policy is in desperate need  for improvement? And is there a way to protect our personal information, when you’re not really given the choice to have your data stored at corporates like Equifax?

 

References

Bogost, I. (2017, September 8). The Banality of the Equifax Breach. Retrieved October 20, 2017, from https://www.theatlantic.com/technology/archive/2017/09/the-equifax-breach-marks-the-end-of-shame-over-data-security/539202/

Fein, R. (2017, October 20). Equifax Deserves the Corporate Death Penalty. Retrieved October 20, 2017, from https://www.wired.com/story/equifax-deserves-the-corporate-death-penalty/

Feng, L. (2017, October 20). After Equifax, New Security Considerations Emerge. Retrieved October 20, 2017, from https://www.forbes.com/sites/forbescommunicationscouncil/2017/10/20/after-equifax-new-security-considerations-emerge/#4ef1e74543ef

Profis, S. (2017, September 16). Equifax data breach 2017: Here’s how to protect yourself. Retrieved October 20, 2017, from https://www.cnet.com/how-to/your-guide-to-surviving-equifax-data-breach/

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Technology of the Week – “Disruption of the Second-hand Car Market” (Group 73)

13

October

2017

5/5 (1)

Back in the day, if you wanted to sell your car, you would usually do it in one of two ways: the first obvious option would be to print out a piece of paper and stick it to your car; the second, to go to several second-hand car dealerships and see what they might offer you. Both these options were very time-consuming and inconvenient for the seller. Also, if you’re looking from the buyer’s perspective, there was a decided lack of information transparency, that might result in you ending up with a “lemon”.

The lemons problem was popularized in 1970 by George Akerlof, and refers to the asymmetric information problem that arises when buyers cannot determine whether a car is a “peach” (high-quality) or a “lemon” (low-quality). Buyers’ willingness-to-pay will then fall around the average value of a peach and a lemon. The peach sellers, who know the true value of their car is above what buyers are willing to pay, will then naturally leave. As more and more sellers of high-quality cars leave the market, the average willingness-to-pay will decrease further, leading to a feedback loop. This adverse selection problem will eventually leave a market full of lemons (The Economist, 2016).

Marktplaats.nl, founded by Rene van Mullem in 1999 (Marktplaats, 2017), helped reduce this information asymmetry by offering an electronic market where buyers could easily acquire information about the price, condition, etc. from different sellers all in one place, reducing search costs.

Marktplaats.nl is an auction site. There are four different types auctions, but the important ones to know here are bilateral negotiation and sales auction, specifically the English sales auction. In the first model, one buyer and seller negotiate to come to a price. In the old situation, a seller would be negotiating with a potential buyer, and if they couldn’t come to an agreement, move on to the next. This selling process can be classified as one or several bilateral negotiations. In the second model, multiple buyers bid increasingly higher prices on a product from one seller, which is how Marktplaats.nl works.

Marktplaats.nl offers the NAP-logo, which signals to the under-informed party, the buyers, that the mileage meter of the car hasn’t been tampered with. This helps reduce information asymmetry. For sellers, advantages include the ease and convenience of placing an advertisement. They are able to reach a broader audience, not as limited by geographical boundaries. Additionally, at different fees they can select the package they want to increase their exposure even more.
In conclusion, Marktplaats.nl disrupted the second-hand car market by offering an electronic market that moved the model typically used in this industry from bilateral negotiation to sales auction, increasing convenience for both buyers and sellers, lessening information asymmetry and thereby partly reducing the adverse selection problem. Our future prediction: Marktplaats.nl will develop more labels and inspections like the NAP, thereby reducing information asymmetry further, consequently increasing buyers’ willingness-to-pay and attracting more “peaches” than “lemons”.

References

The Economist (2016, July 23). Secrets and agents. Retrieved October 13, 2017, from https://www.economist.com/news/economics-brief/21702428-george-akerlofs-1970-paper-market-lemons-foundation-stone-information
Marktplaats (2017). Help & Info. Retrieved October 13, 2017, from https://www.marktplaats.nl/i/help/over-marktplaats/index.dot.html

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Using AI to… shame jaywalkers?

4

October

2017

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Companies and police have for years been working together to catch criminals through IT, but now they’re going further by developing technology to stop criminals even before they’ve committed a crime. Li Meng, vice-minister of science and technology, said that “If we use our smart systems and smart facilities well, we can know beforehand . . . who might be a terrorist, who might do something bad.” (1)

Previously, China’s network of [176 million] surveillance cameras was being used much in the same way as in the U.S., to cross-reference surveillance footage with national ID photographs to catch criminals and terrorists. (2) Over the last years, Cloud Walk, a company headquartered in Guangzhou, has been training its facial recognition and big data systems to assess the risk level of people who frequent weapons stores (but also hardware stores), or transportation hubs. If a person for example buys a kitchen knife now, and a sack and hammer later, their suspicion rating will increase. A high-risk person will be flagged and the system will notify the local police. (3) Their software can also be applied at the train station, where it can analyse the crowd to single out potential pick pocketers.

However, the potential for unjustified arrests increases with this new technology. Legally, charges cannot be brought against someone for a crime they have yet to commit. Li Xiaolin, a partner at Beijing Weiheng Law Firm, states that in practice, even without evidence, a suspect can be charged [with attempting to commit crimes], and that wrongful verdicts are hard to appeal because of the judicial system. (1) Must the judicial system develop more checks and balances before this technology is implemented further?

Additionally, preventing crime is not the only use the Chinese government has found for AI. In dozens of cities, jaywalkers are being shamed. In June, China implemented a new cybersecurity law that protects citizens’ personal information being collected for commercial use, but this doesn’t count for local authorities. Chinese law allows facial recognition to be deployed to “name and shame” traffic light offenders, quite literally. The citizen’s personal information, including names and home addresses, are displayed on screens on the side of roads, reported a local news agency. (2) Furthermore, facial recognition is used in schools to counter cheating, and even crazier, in bathrooms to limit toilet paper waste. (1) Is this going too far?

Still, AI can improve both safety and privacy, online and offline. However many concerns there are about AI being used as a surveillance tool, it can also be used to keep healthcare records private, secure financial transactions, and prevent hacking, for self-driving cars (possibly eliminating at least 90 percent of traffic fatalities). Also, for smart security cameras, robot guards and better military technologies. (3) Although this last one is debatable, as conflicts may escalate more quickly and destructiveness may increase.

In conclusion, AI has great potential for stopping crimes before they happen and improving overall safety, but the flipside is it also has great potential to be misused. What do you think about AI being implemented into society further and further, and not just in China, but everywhere?

1. Yang, Y. (2017, July 23). China seeks glimpse of citizens’ future with crime-predicting AI. Financial Times. Retrieved October 04, 2017, from https://www.ft.com/content/5ec7093c-6e06-11e7-b9c7-15af748b60d0
2. Wang, Y. (2017, July 11). China Is Quickly Embracing Facial Recognition Tech, For Better And Worse. Forbes. Retrieved October 04, 2017, from https://www.forbes.com/sites/ywang/2017/07/11/how-china-is-quickly-embracing-facial-recognition-tech-for-better-and-worse/#b2af19068560
3. Lant, K. (2017, July 25). China’s “Minority Report” Style Plans Will Use AI to Predict Who Will Commit Crimes. Futurism.. Retrieved October 04, 2017, from https://futurism.com/chinas-minority-report-style-plans-will-use-ai-to-predict-who-will-commit-crimes/

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