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Women in Data Science: Being Successful with Artificial Intelligence

By Amalie Widerberg on March 22, 2021
Being successful in applying artificial intelligence

Feature Image: Possessed Photography, Unsplash

It is not a secret that technologies built on Machine learning are all around us. Seeing how healthcare services are offered at a higher speed, how police can identify a larger number of criminals with greater accuracy, or how businesses are able to scale to meet market demands, are all wonderful examples of how we witness innovations benefitting society on a daily basis.

However, the AI solutions that are here to stay are the ones that can solve actual problems. At this year’s Women in Data Science conference in Oslo our Product Director, Janniche Moe, and Head of Customer and Partner Experience, Radmila Stoltz, spoke about the impact that technology can have on our societies, and why innovations like Artificial Intelligence and Machine Learning should not be treated just as a trend but as ways of fulfilling needs.

What is Women in Data Science?

With its first conference being a one-day event at Stanford University back in November of 2015, Women in Data Science (WiDS) has grown massively during the last few years, turning into a global movement including multiple events worldwide.

On Wednesday, March 17th, the Norwegian WiDS conference kicked-off in Oslo. Hosted by SINTEF - one of the largest independent institutes for research and development in Europe - the two-day event was the fifth of its kind, this time completely virtual. The conference seeks to give women in the tech industry a stage and a microphone, making them, their work, and their accomplishments more visible to the public.

In order for technological innovations to be successful, they need to be implemented in a way that considers users of different backgrounds and gender. It is therefore crucial for the tech industry that women have a place to meet, exchange ideas, and network, which is what the WiDS conference offers. However, the conference strives to be inclusive and is open for everyone no matter background or gender.

 

This Year’s Theme: Applied Artificial Intelligence (AI)

Applied Artificial Intelligence (AI) is a prominent trend within the Digital Asset Management (DAM) industry. This is because metadata governance is a crucial element in ensuring a good return on investment (ROI) for any organization and their solution. Effectively, there is a necessity to add a lot of information to an organization's digital assets to make them easily searchable, usable, and sharable. Artificial Intelligence provides an opportunity to significantly speed-up several manual tasks relating to metadata management, as well as ensuring consistency and accuracy across large departments, through image analysis, facial recognition, audio transcription, and automatic tagging. In fact, in our 2020 research on DAM trends, 100% of respondents plan on implementing AI at some point in the future

We need to understand the real customer needs in order for AI to serve its purpose. In their presentation, Radmila shares an example of how it may be a mismatch between customers' needs and technology in the case of making a digital collection of modern art more searchable. While the user expected descriptive valuable information, AI offered instead just recognition of colors. 

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The Importance of asking “Why”

In order for new technology to be fully integrated into society, it must fulfill a need - preferably several. That is why Radmila and Janniche emphasize the importance of asking "why". In starting any development by asking the users about their specific problems, one would have an easier time structuring the innovation to actually solve these issues. This increases the probability that new technologies become more than just trends.

The fact is that AI is really just a pile of data and is only as good as we make it. While Artificial Intelligence and Machine Learning might sound like exciting and important concepts, their value depends on their ability to understand the customer and solve the right problems. In some instances implementing AI to execute different tasks is the perfect solution, while in other situation the tasks and the technology is not a match. By having a clear idea of why you want to invest in Machine Learning, you are able to know beforehand what problems you are actually solving, and whether the investment is worthwhile - or perhaps even more important than what you first assumed.

 

Making a Difference with Technological Innovation

It's no secret that technology enables people and organization to do great things. We are proud to contribute with the technological developments we make at FotoWare, especially when we witness the impact it can have on society.

We see how our solution helps healthcare services, to keep track of huge amounts of patient data, viewing and managing it remotely, while keeping both patients and practitioners safe. And also how it helps police forces to protect our communities, managing their digital evidence more efficiently, and helping to correctly identify and prosecute more criminals to ensure the safety of society.

It is always exciting to make use of new technology to further improve our products, and AI is no exception. But in order to make sure that it is implemented in a way that offers value to users and society in general, we must remember to ask ourselves "why?", so that the technology caters to actual needs and not just personal interest. By also making an effort to include people of different backgrounds and genders in the implementation and development process, these innovations will also truly serve the needs of society as a whole, and further increase its chances of solving problems for everyone, and becoming a part of the structure of society.

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