data mining – The Concordian

AI and human rights forum generates global discussions

On April 5, the Montreal Institute for Genocide and Human Rights Studies (MIGS) hosted the Human Rights and Artificial Intelligence Forum in Concordia’s 4th Space.

“Because we’ve done some work with Global Affairs Canada, the Dutch Foreign Ministry, and worked directly with different companies, we thought ‘let’s try to get a discussion going,’” said Kyle Matthews, MIGS’s executive director, about the event. Panelists from across the globe, some of whom Skyped in remotely, convened to give their expertise on the use of Artificial Intelligence (AI) technology with regards to human rights in different scopes.

“I’m happy we’ve generated discussions, that we’re connecting students and researchers of Concordia to practitioners in private sectors and in government,” said Matthews. “MIGS works on cutting edge issues with human rights and global affairs. We see, because Montreal is becoming the AI centre of the world, that there’s a unique opportunity for us to play a part in elevating the human rights discussion on a whole set of issues and conflicts.”

The Human Rights and AI Forum was held on April 5 at Concordia’s 4th Space. Photo by Hannah Ewen.

Troll Patrol: fighting abuse against women on Twitter

From London, Tanya O’Carroll, director of Amnesty Tech at Amnesty International, spoke about the innovation of AI in researching and crowdsourcing to enforce human rights.

Amnesty Tech’s Troll Patrol was a language decoding program that filtered hate speech towards female journalists and politicians on Twitter. The AI found instances ranging from sexism and racism, homophobia and Islamophobia, and more, with the majority aimed at women in minority groups.

The AI worked in tandem with volunteer human decoders, whom O’Carroll said are an important part of the loop. O’Carroll explained how the issue isn’t that Twitter doesn’t have a terms of abuse policy—it does, and it’s called “The Twitter Rules.” The issue is they don’t have enough moderators, which O’Carroll called their “business decision.”

The AI accurately predicted and identified only 52 per cent of abusive content on Twitter. O’Carroll acknowledged that, while this isn’t perfect, it’s valuable in challenging the data and bringing change to human rights issues on a large scale.

Emerging technologies in the public sector with a human-centric approach

During Enzo Maria Le Fevre Cervini’s panel, the major topic was governance. Le Fevre Cervini works with emerging technologies and international relations for the Agency for Digital Italy.

Le Fevre Cervini said the fourth revolution of AI is based on data gathered from the public sector, which emphasizes the need to focus on the quality and the quantity of data. The ethical dimensions should be less about the technology and more about its product—there needs to be a reassessment of AI as technology that can play a pivotal role in bridging the gap between parts of society.

Prometea, an AI software, quickly processes legal complaints at the DA’s office in Buenos Aires, Argentina. The complaints are compared to similar cases and the accused is either appointed a judicial hearing or not, according to the results. With just the DA computer system, it could take someone 30 minutes to get through 15 documents. With Prometea, all documents in the system are processed in two minutes.

“Technology is a major agent of change,” said Le Fevre Cervini, which is why he hopes governance of AI will change to allow the opportunity for technology to be more human-centred and widely available.

The series of panels was organized by the Montreal Institute for Genocide and Human Rights (MIGS). Photo by Hannah Ewen.

Ethics and AI

“There’s an assumption that AI will be smarter than humans, but they’re just good at narrow tasks,” said Mirka Snyder Caron, an associate at the Montreal AI Ethics Institute.

During her panel, Snyder Caron spoke about behaviour nudging, such as those little reply boxes at the bottom of an email on your Gmail account. While it may be easy, it’s “terribly convenient” because you’re just recycling what you’ve already done—the prompts are based on general replies and your previous emails.

Snyder Caron emphasized that it’s important to remember that AI systems are still just machines that “can be fooled” or “experience confusion.” She gave an example of an AI system that was unable to identify a stop sign covered in graffiti or one with squares concealing part of the word so it didn’t stop.

“Machine learning can adopt status quo based on patterns and classifications because of biases,” said Snyder Caron. To avoid problems such as discrimination, there needs to be increased diversity at the beginning of the AI process. For example, having a diversity of people inputting data could remove a layer of biases.

Bias, feminism and the campaign to stop killer robots

Erin Hunt, a humanitarian disarmament expert and program manager at Mines Action Canada, spoke about the darker side of AI—the dangers, in particular, of autonomous weapons.

With regards to autonomous weapons, aka Killer Robots, Hunt asked: “How are we sure they won’t distinguish atypical behavior?” Because they sometimes can’t distinguish between civilians and combatants, they don’t conform to human rights laws.

Hunt spoke about how biases lead to mistakes, and presented an example of a study of AI identification where 34.7 per cent of dark-skinned women were identified as men. Some AI target people that shouldn’t be targeted, such as people with disabilities. For example, there are regions of the world where people don’t have access to prosthetic limbs and use wood or metal as substitutes. This could be picked up by the AI as a rifle, thus having failed its job.

Technical difficulties with Skype during the panel further enforced Hunt’s point that if we can’t get a simple call from Ottawa to go through, we shouldn’t have autonomous weapons.

Zachary Devereaux (pictured) is the director of public sector services at Nexalogy. Photo by Hannah Ewen.

AI and disinformation campaigns

Zachary Devereaux, director of public sector services at Nexalogy, said there are two ways to train AI: supervised, which “requires human annotated data that the machine can extrapolate from to do the same types of judgement itself,” and unsupervised machine learning, where machines autonomously decide what judgement is necessary.

“Once you see a suggestion from AI as to what you should reply on your email, or once you see a suggestion from AI on how you should complete your sentence, you can’t unsee it,” said Devereaux.

“As humans, we’re so intellectually lazy—automated processes: we love them and we accept them,” said Devereaux. But because of this, the behaviour nudging Snyder Caron spoke about becomes cyclical, such as with Spotify and Google Home. “It’s our feedback to these systems that’s training AI to be smarter.”

AI and the rules-based international order

“Artificial intelligence should be grounded in human rights,” said Tara Denham, director of the Democracy Unit at Global Affairs Canada.

Denham acknowledged that AI makes mistakes, which can enforce discriminatory practices. It is an important question to ask how AI is already impacting biases and how they impact the future, seeing as “the future is evolving at an incredibly fast pace,” said Denham. One challenge is using systems that will amplify discriminatory practices, especially in growing countries who might not have the ability to work around them, according to Denham.

“When talking about ethics, they cannot be negotiated on an international level,” said Denham. Each country has their own ethics framework which may not be accepted or practiced elsewhere. In this scope, it’s important to have a common language and concepts to advance negotiations about human rights globally.

Feature photo by Hannah Ewen

Krzysztof Dzieciolowski shares his passion for teaching and statistics

Krzysztof Dzieciolowski describes himself as a man of two professions, two laptops, two jobs, two locations and two new kittens. However, he’d never want to give any of it up.

For the last 24 years, Dzieciolowski has worked in the telecommunications industry and as a part-time faculty member at the John Molson School of Business (JMSB). “I’m always on the run between them, conceptually as well as physically,” he said, referring to his two jobs.

Dzieciolowski regularly teaches two courses—statistical software for data management, and analysis and data mining techniques—as part of the data intelligence minor at JMSB. His courses allow students to learn the basic concepts and techniques of data management using Statistical Analysis System (SAS), which is the world’s largest statistical software used by many businesses and government bodies. Dzieciolowski also helps students learn data mining techniques using different kinds of data.

Outside academia, Dzieciolowski leads a modeling and analytics group at Rogers Communications, where he helps create predictive models. These types of models are used by businesses to develop techniques for customer acquisition, customer retention and company growth.

“Commercially, companies exist to satisfy their mission to provide returns to their stakeholders,” Dzieciolowski explained. “So in a way, we help companies, using math, become more effective in generating profit, as well as be more cost effective, and providing the products and services to customers.”

Using mathematical and statistical models, Dzieciolowski works to define “events of interest,” such as making a sale, acquiring a new customer or losing a customer, and relate such events to that customer’s profile. Dzieciolowski and his team can compare the profiles of customers who did or did not experience any given event of interest, and their behaviours prior to this event or non-event, to see if a correlation exists between a given profile or event.

Using this data, Dzieciolowski is able to create a model, such as an equation which relates independent variables to the observed event, that can help Rogers predict the probability on a scale from zero to one of a given event of interest, such as making a sale. This probability score allows Rogers to know who is likely to purchase a product from the company. These tools are very useful for marketing and sales, but also benefit customers by providing them with better and more relevant service.

“It boils down to a simple question—who should we talk to, what about and why?” Dzieciolowski said. “I like challenging questions, and my colleagues in the office keep me busy, whether they’re from marketing or product sales or finance. They often come to ask me a variety of questions which are fairly complex. I enjoy working with them and solving those questions together, whether it’s related to mathematical aspects of the solution or whether it’s actually on the applied side.”

Another challenge Dzieciolowski has always enjoyed is teaching, which has always been important to him. When he was living in Poland during the 1980s after having completed his master’s degree in mathematics at the University of Warsaw, Dzieciolowski worked for four years as a math teacher and social worker at a high school for inner city youth who had dropped out of regular schooling and were at risk for using drugs.

“That was a great experience,” Dzieciolowski said. “I was not much older than my students. I was 25.” The school was funded by Poland’s Ministry of Education and Behaviour, but the ministry maintained an arm’s length relationship with the school because, according to Dzieciolowski, they would not officially acknowledge the country’s heroin epidemic.

Dzieciolowski’s young age made teaching an even more rewarding experience. “We were socializing with them as well, by taking them to camps, school cinema which I used to run, also ski camps and cooking together in the kitchen and cleaning up everything afterwards,” he said. “We had a lot of common activities, and it was a fun place to be.”

During this time in the 80s, Poland’s communist government had put the country under martial law. “I was trying to find a job, but as a non-party member, I didn’t have much of a chance to land anything,” Dzieciolowski said. “I finally decided to come to Canada to do my PhD and follow in the footsteps of my colleagues who were also grads of mathematics and also went abroad to continue their studies in Canada or Europe.”

While studying at the University of Warsaw, Dzieciolowski joined a quantitative seminar in the sociology department. It was there that he was introduced to the quantitative applications of math, which Dzieciolowski explained can be used to model social events, social phenomena and social patterns.

“I discovered that I have an interest in real-life applications and how people use math and how their lives and their social lives can be described using mathematics,” he said. “So it was natural to turn to statistics.”

Dzieciolowski started his PhD in statistics at Queen’s University in Kingston, Ont. Three months before completing his PhD, Dzieciolowski was offered a position at Bell Canada in Montreal.

“I had to quit my studies and move to Montreal and start the job in three weeks. It’s always like this in the business; when they have an opening, it’s always for yesterday. I took the job and I became a part-time, off-campus student and finally finished my thesis two years later,” he said. “Professionally, I think it was a good thing to do because I really enjoyed applied work.”

In addition to the job offer, Dzieciolowski said his decision to move was greatly influenced by Montreal itself. “The reason why [my family and I] came to Montreal was mainly because of the lifestyle and culture the city offers, which is so close to our experience in Europe.”

Several years later, Dzieciolowski was offered a position as a part-time faculty member at Concordia, which allowed him to rekindle this love of teaching.

“The best part is interactions with students and creating a fun environment to learn. I think I promote a lot of teamwork in the classroom. Sharing and presenting and having a learning experience without necessary stress is a great achievement, I think, and I’m always striving to get to that point where people are learning in a stress-free environment,” he said.

Dzieciolowski said his teaching style focuses on allowing students to learn the material on their own, so they are more motivated and interested in the topic. “My role in the classroom is really to help them learn how to learn. We are in it together.”

Dzieciolowski has accomplished a lot during his time at Concordia. One of his proudest achievements, he said, was creating the joint undergraduate certificate between JMSB and SAS in 2016.

“I’m very happy about this, and a lot of students ask about it. We will have another batch of students graduating with this certification this year as well,” Dzieciolowski said. “We’re collecting applications from last year and this year to jointly award them together sometime in May or June.”

Students interested in the certificate must apply to the department of supply chain operations management within JMSB and successfully obtain a B in four out of five option classes. “I’m happy to say I teach two of those classes, and students show a lot of keen interest in learning new methodologies and new thinking and new applications of statistics in data science,” Dzieciolowski said.

“The joint certification means we are now able to use the state-of-the-art statistical software, which has been installed in our labs without fee. Students are learning the leading data mining software that is widely used outside, and they’re getting ready for the jobs that are there which require them to know SAS and understand the business problems the software is helping to solve,” he said.

Dzieciolowski was recently the recipient of a $10,000 Special Project Award from the Concordia University Part-time Faculty Association (CUPFA) to conduct research into new predictive methodologies and data matching techniques while at Rogers last year. On March 22, Dzieciolowski presented this research, his experience teaching data science to students, and his proliferation of data science applications and artificial intelligence during a talk at JMSB.

Dzieciolowski’s research explored how to create predictive models when a company doesn’t have access to information about all events of interest. “In practical terms, you may think about two different databases that have to be connected or merged together, and those databases are often disconnected and do not talk to each other. The only way to identify if the customers have both accounts would be to merge the data based on their name or address,” Dzieciolowski explained. “But those kind of merges often produce incorrect results. So we think they do have both accounts or they don’t, which is a false positive, or they do actually but we classify them as if they didn’t, which is an example of a false negative.”

Dzieciolowski’s research focused on how to create predictions when confronted with such “fuzzy merges,” and on determining how misclassifications impact the quality of the predictive models. “It’s very much applied, very much up-to-date and of great interest to large companies, whether they’re from telecoms or business, because there’s always a need to conduct those fuzzy matches between the data sources,” he said. “Therefore, there will always be an interest in making sure we predict what we want to predict.”

Although Dzieciolowski enjoys being a part-time faculty member, he said that status has caused some difficulties over the years. “I never had a chance to get a grant, for example for hardware, even though I do conduct research as well as teaching,” he said. However, this is the only disadvantage he has experienced as a part-time professor at Concordia. “I’ve been a part-time professor since day one 24 years ago. I never had an issue getting courses to teach, especially since I teach the data mining classes which not many people are interested to teach for some reason or another,” Dzieciolowski said. Nonetheless, he appreciates that other part-time professors experience job insecurity.

“As you can see I’m a pretty busy person,” Dzieciolowski added with a laugh. Despite his busy life, Dzieciolowski makes time to travel, recently adopted two kittens, and stays in touch with his former students in Poland. “I keep in touch with many of them on Facebook. They discovered I still exist a few years ago and we reconnected,” he said. “It’s all a very rewarding experience.”

Photo by Alex Hutchins