A research study by The National Center for Women & Information Technology showed that “gender diversity has specific benefits in technology settings,” which could explain why tech companies have started to invest in initiatives that aim to boost the number of female applicants, recruit them in a more effective way, retain them for longer, and give them the opportunity to advance. But is it enough?
Three years ago, we launched a diversity series aimed at bringing the most inspirational and powerful women in the tech scene to your attention. Today, we’d like you to meet Dr. Susanne Genzel, Data Label Manager at i2x.
Today’s Woman in Tech: Dr. Susanne Genzel, Data Label Manager at i2x
Dr. Susanne Genzel is Data Label Manager at the Berlin-based start-up i2x. i2x is a speech recognition technology for
the German and English languages. It analyzes complex conversations using artificial intelligence in real-time. The program automatically generates training units tailored to individual development areas to optimize sales and service conversations. Using i2x technology, employees and self-employed persons can transcribe telephone calls and evaluate the course of conversations using machine learning. i2x is the first speech recognition and training technology of its kind in the world.
When did you become interested in technology?
You would think I was technophobic: I have no vacuum cleaner, no car, no computer and no microwave. But I like to experiment.
Technological interest arises for me whenever recurring processes occur that I can automate. This is possible, for example, with measured values from large data sets, which can be automatically extracted and statistically evaluated. Through a HiWi job during my linguistics studies, I got to know the software “Praat” and performed phonetic analyses. During my diploma thesis, I used R for statistical analysis.
Do you have any role models?
In my private life, I am surrounded by strong women. Pippi Longstocking with her attitude to life is also one of my role models. Björk also inspires me on a musical and artistic level.
Professionally, Prof. Dr. Frank Kügler “discovered” me very early on and we worked together successfully from 2003 to 2019. He has always supported me, encouraged me, and placed a lot of trust in me. My doctoral mother Prof. Dr. Caroline Féry has also had a strong influence on me. In her seminar on prosodic typology, I acquired an incredible amount of know-how that I was able to apply in the creation of language corpora and on field research trips.
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What did your career path look like?
Before I came to my current job at i2x, my focus was mainly on research. But one thing at a time: After a few detours, in my early twenties, I came across the study of general and theoretical linguistics at the University of Potsdam. The mixture of psychology, philosophy, communication, and cognitive sciences sounded very exciting.
Due to my HiWi activity in the field of phonetics/phonology I was in contact with data and its evaluation at an early stage, so that I could experience research first hand. When I was about to quit my studies in the fifth semester – the topics became more and more abstract – I (fortunately) attended a seminar by Rama Kant Agnihotri on the socio-linguistic situation in India. This impressed me enormously and gave me a perspective. After my diploma in 2007 (“Phonetic realization of focus on adjectives in Hindi”) I went into research. My main focus was the analysis of the interaction of information structure and tonal structure and its phonetic realization in a comparative language perspective. In 2013 I received my doctorate on “lexical and postlexical tones in Akan” and worked as a post-doc at the university before I had my two children.
My doctoral mother Prof. Dr. Caroline Féry has also had a strong influence on me. In her seminar on prosodic typology, I acquired an incredible amount of know-how that I was able to apply in the creation of language corpora and on field research trips.
The tangible merits of a researcher are his publications. Each paper is preceded by a long process that can be described as a separate project. It usually takes years to go from research, hypothesis development, and experimenting to the evaluation of the collected data and writing. The probably biggest project was my doctoral thesis on “lexical and post-lexical tones in Akan”. It is one of the first experimental phonetic works on prosody in the African tonal language Akan.
Since a professorship was out of the question for me and I would have found pure research in connection with my motherhood too eremitic, I decided after 12 years of academic career to try my luck in the free economy. In my job interview at i2x, I immediately felt comfortable. The work culture and team size fit, and I also liked the internationality of the colleagues. But in the end, the very good thematic fit was decisive.
A day in Susanne’s life
As Data Label Manager I act as an interface between call data and machine learning. Labeling is an essential part of data processing for supervised machine learning. Through labeling, data is assigned to a specific category. The labelled data is used to train and optimize algorithms. So my main task is to ensure that high quality data is available in sufficient quantity for the machine learning process. I support different teams in the implementation of ideas and projects. The main focus is on the question of how certain concepts can be quantified or extracted from the data. I also manage the team of in-house labeling agents and oversee the entire labeling process – from the idea to the creation of the labeling task in the labeling tool to the distribution of the labeling tasks.
In addition, I am realizing my own project on communication skills. This project is about making the communication skills of the participants of a conversation measurable. This includes, for example, verbal, social and emotional skills. These are analyzed on a textual and supra-segmental level. Here, I not only look at what the call center agent says, but also evaluate the interaction with the caller. My goal is to make the compositional interpretation of meanings from text and prosody machine-learnable.
Every working day looks different. I research a lot of technical literature, prepare data for labeling and design my own experiments. In addition, I have meetings almost every day, which I prepare and follow up.
Why aren’t there more women in tech?
Many different factors influence the fact that women are underrepresented in the tech industry. Working hours in many companies are not very child-friendly. In addition, the environment or culture “inherits” the socially anchored stereotypes from one generation to the next. This begins at home and is continued in the educational system: Educators and elementary school teachers are mostly female. In terms of stereotypes, it is rather unlikely that a female reference person will program a computer or disassemble a smartphone. Unfortunately, this often leaves technical affinity among girls undiscovered or is not encouraged.
When men take on the role of caregivers, this automatically leads to children being confronted with more with hobbies that are perceived in society as primarily “male”. This must therefore be the goal in order to achieve a long-term balance.
In general, I am of the opinion that hurdles are there to be jumped. If someone feels discriminated against, I would advise them to address this directly.
Would our world be different if more women worked in STEM?
Diversity is incredibly important, because diversity is enriching. I am thinking here of different age groups, genders, nationalities, life paths, etc.
In science, there was often a woman behind every great scientist, who also played a decisive role. Women are present, but often not in the front line. This has social and also biological reasons. It is the women who have children, which leads to an imbalance. 46% of the employed women work part-time for family reasons, often in addition to family management. This makes a classic career difficult.
Women often bring a different perspective to the social structure within a company. At i2x, for example, I have suggested that regular coffee dates be set up to get to know each other better, as well as a buddy program. Neurobiologically, women have different problem-solving strategies than men. The combination of the different approaches is therefore recommended.
Because I am not a techy in the classical sense, I can approach problems with complete freedom. I think less about the implementation than much more about the concept behind it. But this has nothing to do with the fact that I am a woman, but is a general plea for diversity. Also economically, in product development, a diverse team should always be involved. Because most products should not only work for men of a certain age, but for a large target group.
Whenever it comes to user-friendliness, as many different people as possible should have a say. The same applies to the programming of artificial intelligence and to any area that has to do with emotions. The entire whole of society must be represented.
What does the future of the diversity debate look like?
I don’t think that the diversity debate will be history any time soon, because we are just at the beginning. Inequality on the labor market arises above all when women have children and take on the role of mothers. Fortunately, our society is on the way to strengthening men in their role as fathers as well. Fathers should not only be providers, but also active parents. However, there is still much room for development, especially in the free economy.
The good thing is that the topic of equal rights is being discussed more and more often – at least that’s how it is in my circle of acquaintances.
The good thing is that the topic of equal rights is being discussed more and more often – at least that’s how it is in my circle of acquaintances. Awareness is a first step towards bringing about social change.
Has anyone deliberately tried to put obstacles in your way?
No obstacles have been put in my way – not that I know of them. There are certainly clichés about women in general, but vice versa, this also applies to men, different nationalities, certain age groups etc. Every person is unique and has his or her strengths and weaknesses. In my eyes there is also no generally valid cliché about “Techies”. In our Machine Learning team, for example, there are people with very different backgrounds and characters (social scientists, mathematicians, physicists, economists).
What advice (and tips) would you give to women who want a tech career?
The first step is the most important one: Just go to interesting companies and see if the total package fits you personally.
It is difficult to make a general educational statement about what other girls and women should know about working in the tech industry. About i2x I can say that I have found the perfect job for me here. The people in our Machine Learning Team all have an academic background, which is a very good basis for working together. I feel valued here and can fully contribute my expertise.
More Women in Tech:
- Women in Tech: “Dare to do what you are interested in!”
- Women in Tech: “Join meetups and other women tech groups”
- Women in Tech: “The IT sector requires a lot of energy and will”
- Women in Tech: “I got to be a self-taught, self-managed, problem solver”
- Women in Tech: “Don’t let irrational advice keep you from tech!”
For even more Women in Tech, click here
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Source : JAXenter
