Hiring Process – Double Information Asymmetry

9

October

2021

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Hiring efforts can be considered futile when a freshly on-boarded employee decides to leave the company after barely a month of two of trial. However, recently companies have come to the conclusion that these mishaps might be due to a reason other than the fault of the specific individual that decided to leave the company.

Many of you probably know this already, hiring processes nowadays are extremely complex in their format. Usually composed of a multitude of stages from interviews to technical tests, the average hiring process takes about one month to be complete. The essential lesson here is that if a person decides to leave during their trial period, it is not due to a lack of motivation as they had the will to through the entirety of the hiring process in the first place.

The problem that was investigated was an instance of double information asymmetry.

On the job seeker perspective, the candidates have the advantage of knowing exactly what is sought after by the companies. By analyzing the job description, a person could precisely determine what experiences, traits of character or values that the company is looking for. Usually, by exploiting this information, the candidates will personalize and modify their profile in order to meet the employer’s wants. This is a case of Morale Hazard as the misinformation is conducted prior to the transaction, i.e. hiring that person, under the form of signaling the employer with non-representative characteristics.

On the other side, from the point of view of the employer within a company, the job description will also be an altered version of what the real job is. The Morale Hazard here is also done through signaling, by misrepresenting the core job functions in order to attract as much talent as possible. For example, stating that the job’s missions are usually 50% administrative tasks and 50% project management tasks while in reality the ratio might be closer to 80-20.


Interviews are used as screening tools to try to separate the most suited candidates from the least suited. However, these tools can prove to be less effective than expected as the interviewee can easily prepare for it in a non-truthful way.

Here we mention ‘non-truthful’ or mention how sneaky it might be to exaggerate about your profile, but the candidates cannot be blamed. The double information asymmetry happens because there is also an asymmetry of goals.

On one side, the goal of the job seekers is to get the job. It is not to ‘enhance the company’s growth’ or ‘help them in their mission’ as commonly stated during interviews, but often it is simply to get hired. And on the other side, of course the company’s goal is to find the best person for the job at a reasonable salary.

An interesting solution to put an end to this information asymmetry would be to use platforms that accept only one resume per candidate (instead of one per job application) and where details about the job description are revealed later, such as during the first interview.

What are your thoughts and ideas to tackle this information asymmetry?

Resources:
LinkedIn post that inspired me (in French):
https://www.linkedin.com/feed/update/urn:li:activity:6851817268762968064/

Article for further discussion:
https://www.business2community.com/human-resources/how-to-crush-hiring-by-recognizing-information-asymmetry-02251645

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Botnets and Smart-houses: Attack on Philip’s Hue Bulbs

15

October

2017

No ratings yet. What is a botnet?

It is a collection of devices which are all connected to the internet, where each one is running one or more bots (autonomous program). These include any type of device that can be controlled by malware. Most of the time, the owners of these devices do not know that their devices are infected.

But why is this topic becoming more important? With more variety and cheaper devices becoming a part of ‘the internet of things’, there is a larger pool of devices which can be infected. Since many of these devices have very little security, they are easily infected and large networks are quickly made.

So, what can the hackers do with these botnets? They can take down websites with large DDoS attacks (you may have experienced these playing online games), that take down the servers by flooding their bandwidth using botnets. Secondly, they can commit click fraud, where advertisers online are led to believe people are clicking their ads. This could ultimately destroy the internet advertising model. Furthermore, they can use these their botnet network to mine bitcoins (and earn a considerable amount of money doing so).

However, another type of attack is equally frightening. The smart-LED-light system from Philips, the Philips Hue is just as vulnerable to attacks as any other device connected to the internet. These Hue lights allow the user to control their lights via the internet, with a lot of different functions. With more people adopting these type of technologies (myself included) large scale attacks can have serious effects.

Researchers from Canada were able to remotely hack hue bulbs from a distance of 70 meters using botnets, allowing them to control them. Not only is this something you obviously do not want as a consumer, but it can seriously damage an electrical grid of a densely populated area. This was all done with equipment only costing a few hundred dollars. Although the researchers worked together with Philips to improve their system, similar attacks may follow.

The Hue lights are only one aspect of a smart house. When more devices are added to your house for convenience, a hack can do a lot more damage. As a consumer who enjoys these technologies a lot, I am left to trust these large companies to improve their software to keep me protected. But to what extent can these technologies put me at risk? Are you willing to trade the risk of being hacked for the reward of  “super cool lights”?

https://www.technologyreview.com/s/603500/10-breakthrough-technologies-2017-botnets-of-things/

https://www.cnet.com/news/new-study-details-a-security-flaw-with-philips-hue-smart-bulbs/

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Let The Sun Shine!

24

October

2016

No ratings yet. When it is cold outside, you will most likely put on a warm winter coat. And when the sun starts shining, the ice cream sales skyrocket. This may seem evident, but connecting sales data to weather information can be very insightful. The weather influences our purchasing behaviour much more than we could even imagine. Do you know how? Let’s find out.

Purchase channel
One obvious influence the weather has, is the channel we use for our purchases. On sunny days, bricks-and-mortar stores enjoy more footfall, while online turnover increases on rainy days. However, the influence of rain is industry dependent [1]. On rainy days there was a 12% increase in website traffic for retailers in the home & furniture, wholesale, and clothing verticals. However, there was no significant difference for big box retailers.

This is interesting, unfortunately the studies do not reveal the underlying reason. I think it has to do with different products reacting differently to weather change. As big box retailers have a big variety of products, the fluctuations are more likely to cancel each other out.

Mood change
Temperature, air pressure, humidity, snow fall and sun all have an impact on people’s mood. These moods reflect into different purchasing behaviours. On sunny days, people tend to be more opportunistic in their purchases. For example, more cars are sold on hotter days. On the other hand, during hurricane seasons, people book more holiday to resorts in exotic destinations.

This is not only shown in economics. Different moods, caused by the weather, also change your chances in romance! The French psychologist Nicolas Gueguen initiated an experiment in which an attractive male approached unaccompanied young, asking their telephone number [2]. “I just want to say that I think you’re really pretty,” he cooed. “I’ll phone you later and we can have a drink together someplace.” Antoine achieved an impressive success rate of 22% on sunny days but only 14% when it was cloudy.

Conclusion
Obviously, fluctuations of the weather are influencing shopping. However, the influences reach further than I expected myself. Another eye-opener is how easily we can connect all these kinds of situational factors’ data to already existing data, to find new insights. Do you have any suggestions for different situational factors, to elaborate on?

References
[1] http://www.richrelevance.com/blog/2012/08/what-happens-with-online-shopping-when-it-rains/
[2] http://www.sciencedaily.com/releases/2013/01/130128081950.htm

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AIVD reading your Whatsapp messages?

10

October

2016

5/5 (10) This year Whatsapp decided to use end-to-end encryption for all whatsapp messages in following of their concurrent Telegram. This to protect the privacy of all users and ensure the users that their private messages keep private.

This week Rob Bertholee, the CEO of the AIVD (Dutch national security agency) spoke out in an interview that the AIVD wants the power to crack the encryption of Whatsapp. According to the AIVD the increasing use of information-encryption leads to problems regarding to the prevention of terrorism. The ideal situation for the AIVD would be to have an oversight of the whole criminal network, provided by their phone network history.

But of course this raises again the security versus privacy discussion. How much privacy is your safety worth? Should the AIVD have insights in everyone’s personal messages to protect the country?

History doesn’t prove that spying is the right solution. Before Whatsapp decided to encrypt their messages, people made use of PGP (Pretty Good Privacy) telephones. The government got the rights to crack these and since then they use them as prove in court for criminal cases. This should make the process more easy, but has so far disappointing results. A lot of criminals use aliases to stay anonymous and if they handled secure, the messages weren’t retraceble.

I would like to plead that privacy is not dead (yet) and that analyizing personal messages isn’t the right solution to protect citizens. Privacy is crucial for self-identity and autonomy. (Focault, 1977) (Wolf, R. D., & Heyman, R. ;2015).

“Privacy is the claim of individuals, groups, or institutions to determine for themselves when, how, and to what extent information about them is communicated to others” (Westin, 1968).

Also if the AIVD gets access to the messages, it is not sure how they’ll analyze the messages. Which false-positive ratio would be acceptable? And for what extend of time can they store the information? Another raising question is how they can ensure the security. Once there is a crack, the security of the messages is much harder to maintain.

What do you think? Would you let the AIVD read your messages? Does privacy still excist and if so, where do we draw the line?

 

 

http://nos.nl/artikel/2132835-aivd-plan-om-versleuteling-whatsapp-te-omzeilen-veel-te-gevaarlijk.html                  

Wolf, R. D., & Heyman, R. (2015). Privacy and Social Media. The International Encyclopedia of Digital Communication and Society.

Foucault, M. (1977). Discipline and punish: The birth of the prison. Vintage.

Westin, A. F. (1968). Privacy and freedom. Washington and Lee Law Review,25(1), 166.

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Your Romance Is So Boolean…

8

October

2016

3.89/5 (19) Chances are big you have ever tried an online dating application. Or at least considered one. It no longer is a taboo if you met your fiancée through the world wide web. Online dating applications such as Tinder, OkCupid and Match have millions of users per day. They range from testosterone driven adventure seekers to incurable romantics. Nonetheless, they are all searching for the perfect match.

In the quest of finding this perfect match, users have many conversations and look at even more profiles. This creates an enormous amount of valuable data. But how can we use this data? Will data analysts become the new Cupids and brew love potions? Is it even possible to catch abstract concepts such as love and romance in algorithms, in order to find a perfect match?

According to Christian Rudder, founder of OkCupid, the problem is not in the algorithms, but in the data itself: “My intuition is that most of what users enter is true, but people do misunderstand themselves.” That is where big data comes into play. Why would we ask people to fill in questionnaires, would it not be better to find this data statistically?

Nowadays, we know so much about a person through analysing their behaviour on the internet. On a dating profile, one can easily state he loves classical music. However, his Spotify-history or iTunes purchases could reveal he actually listens to pop music most of the time. Everyone knows how important a first impression is. If you are not into snobs, why would a dating applications even bother to show people with a Ralph Lauren loyalty card?

Big data offer enormous opportunities to online dating application. At the same time, these opportunities raise serious issues. What about privacy concerns? How will such an influence affect people’s social skills? Would you like to be introduced to your future wife by your computer?

 

References:
http://www.bbc.com/news/business-26613909

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