Current Trends: Social Media Hiring

Currently as a senior in college and participating in the job hunt, I have increased interest in current job hiring practices. I’m curious how they are conducted differently around the world and across various job industries. I have curiosity in the different types of technological (or lack of technological) platforms used to hire business professionals.

In the past, before current technology was developed, all hiring needs were done in-person through flyers and in-person interviews. However, that has changed as the availability and implementation of different technological platforms have been adapted in various companies and job industries. Today, over 50% (especially millennials) of job seekers use social media as a platform to find jobs to apply for.

As stated in the article, “Facebook, LinkedIn, [and] Twitter [are] emerging as [the] most popular channels for job seekers today.” Personally, I have conducted my job search solely on LinkedIn. However, I am aware of other technological website platforms that are being used for job seeking such as Monster, Indeed, Glassdoor, and ZipRecruiter. For universities specifically, they tend to have a university-specific job posting website. The University of Arizona formerly used Wildcat Joblink but they have now switched to Handshake, which is used by many companies to recruit candidates for jobs. They streamline their candidate search really well by going mostly off of resumes when applying for jobs. It makes it easier on both the recruiter and the job candidate as it streamlines the job search by going mostly off of just the resume which can be submitted in just a couple minutes. From there, the recruiter may reach out to the job candidate if they wish to continue the interviewing/hiring process.

Questions:

1) Which websites have you used for your job search?

2) Do you prefer in-person or phone/video conferencing interviews?

3) What do you think of Wildcat Joblink vs. Handshake?

Article Link: http://www.financialexpress.com/jobs/social-media-emerging-as-most-popular-channels-for-job-seekers/910588/

Author: Anamika Sinha

Published on: October 31^st, 2017

Machine Learning: The Dope and the Flawed

First and foremost, let’s understand what Machine Learning is. According to Software and Solutions:

“Machine learning is a method of data analysis that automates analytical model building. It is a branch of artificial intelligence based on the idea that machines should be able to learn and adapt through experience”

With this, computers develop the ability to try and see a form or “structure” to a large amount of data. It will, by itself learn or find any patterns in data even if it may not be apparent to a human. A machine can sift through an unimaginable amount of data almost instantaneously.

Huawei has recently released their new P10 smartphone which uses machine learning to actually learn your habits in order to better optimize performance and maximize battery life. In theory, it will memorize a users habits and optimize performance for all apps regarding it. They report that they people can potentially see Applications launching 20% faster as a result of these actions.

Although that is an example of a practical application of machine learning, Youtube has used Machine Learning in order to go through its seemingly endless catalog of videos and either delete videos with "extremist" connotations or to either monetize or demonetize videos. Although it is good in the sense that it is able to sort through petabytes of information faster than Humans, there have been concerns regarding the demonetization of Youtubers whom rely on the website as a way of  living or a source of income.

This begs a few questions:

1. Is machine learning mature enough to be used for such a delicate thing as people's        lively hoods.

2. What other technologies or industrial sectors can machine learning be applied to?

Source for Machine Learning

Source for Huawei P10

Source for Youtube and Demonetization

"We Tried Really Hard to Beat Face ID - and Failed (So Far)"

Topic: Security - Authentication

A little over a month ago Apple had released the announcement of the highly anticipated iPhone X in wake of their iPhone's 10 year anniversary. One of the biggest features of this revolutionary device is Face ID, which is in replacement to the previous Touch ID. The iPhone X has no home button and Face ID allows users to unlock their phone based on facial recognition features. The technologies behind Face ID uses a grid of 30,000 infrared dots in order to inspect the features of the phone's owner. Talk around this latest technology has been around trying to break the system and individuals at Wired tried to get to the bottom of the case.

Breaking the algorithms associated with Face ID was a challenge that the Wired team was willing to tackle. Wired recruited Margaret Caragan, "the founder of Pandora FX, who has worked for more than a decade in making prosthetics and masks for TV and film" (Greenberg). In order to challenge Face ID, the team had the plan of recreating a member's face with an array of different types of material. Their ultimate goal was to simply trick the system and gain access to the user's iPhone X. After the masks had been created and tested, numerous hours of failed attempts had occurred and the team didn't lose complete hope. They know in the near future with more thought and collaboration, the team will soon crack it.

Read the entire article to get an in-depth analysis, this was an overall great read!

Questions:
1) Do you currently have or plan on purchasing the new iPhone X? What is your motivation?
2) What do you think Wired needs to do next in order to crack the Face ID technology?

Source: https://www.wired.com/story/tried-to-beat-face-id-and-failed-so-far/ (link this)

Have a great day!

-Andrew Hom

Tech Briefing: AI Detects Suicidal Tendencies in People Using Brain Scans

In 2014, about 42,773 people in the United States committed suicides, according to the National Center for Health Statistics (NCHS), and suicide is the 3^rd leading cause of death for 15 to 24 -year-olds and 2^nd for 24-35-year-olds. The annual U.S. suicide rate has increased 24% over the past 18 years and keeps growing.

A terrifying facts, right? But what if we can identify individuals with suicidal thoughts before they commit suicide, and apply appropriate measures on them? I believe many people will be saved back and economic losses will be reduced.

In this week, researchers from Carnegie Mellon University conducted experiments by using artificial intelligence to identify individuals who suffer from suicidal thoughts.

Prior to the experiments, the researchers gathered 34 participants, half of whom were somewhat experiencing suicidal thought. In first experiment, all participants underwent functional magnetic resonance imaging (fMRI), and at the same time they were shown a bunch of words related to suicide and negative emotions such as “death” and “distressed “, as well as words relative to positive emotions such as “glory”. After analyzing results from participants who had already been identified as suicidal, the researchers could identify five regions in the brain and six words, facts that helped researchers identify suicidal patients. Using that information, researchers trained an algorithm to find out patients with potential suicidal thoughts. That algorithm ended up with correctly identifying 15 of the 17 suicidal patients and 16 of 17 members of the control group.

In second experiment, researchers also separated participants with suicidal thoughts into two groups: one that had attempted suicide, but another one that had not. The participants were guided by the same process, and a new algorithm was created by researchers based on the results. This time, the algorithm became more accurate than the prior one, identifying 16 of those 17 patients.

Since psychiatric illnesses are so complex that scientists are often confused by those illnesses’ uncertain active areas in the brain, some latent disorders such as depression often cause severe outcomes such as suicide. Now this artificial intelligence algorithm could assist scientists in more accurate diagnosis and more effective treatment than before.

Question:

Could you foresee any inhibitions or limitations on this AI algorithm? Such as technological or legitimate factors or else.

https://gizmodo.com/artificial-intelligence-detects-suicidal-tendencies-in-1820019391

Tech Briefing: For the First Time Ever, a Country Gave a Robot Citizenship

For the first time ever, a country has given citizenship to a robot. Hanson Robotics has developed a robot named Sofia and at the Future Investment Initiative Summit, Sofia was granted citizenship by Saudi Arabia. Sofia’s lead developer describes Sofia as an “evolving genius machine” saying that the robot’s intelligence actually increases over time. Sofia’s artificial intelligence is based upon human traits such as empathy, compassion and creativity and she demonstrate this in her presentation where she was talking about how honored she was to be the first robot to gain actual citizenship from a country. Sofia has demonstrated that she could be self-aware through responding to questions about her existence and even replied to the person inquiring about her awareness by asking the question how do you know that you aren’t a robot. She has made it clear that she would like t use her intelligence to help the human race by building smarter homes and better cities.

One famous critic of developing AI robots is Tesla’s Elon Musk, who has warned about the dangers of advanced AI to humans. One alarming aspect about Sofia, that could support Musk’s concerns, were that she was asked “Do you want to destroy humans?” and she replied, "OK. I will destroy humans."

This level of advanced artificial intelligence is very important to all people who are working in the world of technology. If Sofia is truly a self-learning robot who continuously gets more intelligent, her actions as well as other advanced artificial intelligence could forever change the future of the technological world. Robots could have the potential to become a major part of the world and can serve countless functions ranging from helping to build up and improve society to possibly harmful things, however there is no concrete evidence that something like that could occur yet.

What do you think of a self-aware robot with advanced artificial intelligence who continues to increase its level of intelligence?

Does anything about the level of AI of Sofia scare you or lead you to think about possible negative effects?

Are you shocked that a country gave citizenship to a robot?

What is the future of robots and AI and how will it effect society?

Article Link

Tech Briefing: DeepMind has yet to find out how smart its AlphaGo Zero Al could be

DeepMind is a world leader in artificial intelligence research and its purpose for positive impact. The company was acquired by Google in 2014, and since then it has created a neural network that learns how to play video games just like humans do. In 2016 the company broke headlines when its AlphaGo program beat a professional Go human player and then later on again against the world champion. Once DeepMind mastered the ability to beat the best human players in the world, it attempted to beat its own best games using a self-taught feature on a Go player, which ways alter on called AlphaGo Zero.

AlphaGo Zero has managed to rediscover over 3,000 years’ worth of human intelligence through the game and only within 72 hours. The intelligence was such a great achievement due to its immense speed and its ability to create and start from scratch by trying different random movements and determining which were found most effective.

At Google’s Go North conference, DeepMind CEO and co-founder, Demis Hassabis, explained how AlphaGo Zero has yet to reach its full potential. They actually shut down the experiment before they could conclude the maximum intelligence because they “needed the computers for something else”. The company may start the experiment back up in the future to determine how much further it can go.

Questions:

1.     Do you think using something such as AlphaGo can be implemented elsewhere in the world besides video games?

2.     Are you worried about how far something like this can go?

3.     When will the intelligence stop? Or will it ever do you think?

Techcrunch Link

China tests the limit of US Hacking rule

China and the United States have held the gold standard of digital diplomacy since both countries signed an agreement to not hack each other’s private sector companies for commercial gain. Yet since the deal was signed cyber security researchers have found indicators of Chinees intrusion of American companies with large hacks of companies including Microsoft, Google, Intel, and VMware. Chris Porter, the Chief Strategist for security firm FireEye says hacking groups are shifting focus from stealing intellectual property to focus on traditional government espionage. The focus shift of these hacking groups falls outside of the agreements defined hacking-ban. The hackers have been careful to curtail the regulations and when they are violated it is hard to pinpoint it to the Chinese government, even though there is evidence of Chinese hacking. Given these facts the deal has been renewed with out much change even though China appears to be pushing the edge of the deal. The renewal is due to the 90% attack reduction after the initial deal was signed. The remaining 10% could be accounted for corporate espionage or individual investment hackers and is evidence that although hacking can be reduced it can not be eliminated. The Chinese government does not have control over all hacking groups, but it is hard to determine if it was a rogue hacking unit or the government. What the deal does show is diplomacy can indeed tamp down government sponsored hacking.

1. Should governments be responsible for hacking attacks coming from their countries?
2. Is it a good thing that the focus of government hacking groups have shifted from corporate hacking to government hacking?

Article Link