The Tech that comes next

Afua Bruce and Amy Sample Ward

Book review

Here at the IoA we are already turning our attention to the end of year IoA awards. We know some analysts in our community work for the betterment of society, and we’ll be looking for your nominations soon.

If you need some inspiration for tech for social good, a new book, The Tech that Comes Next, offers plenty of ideas and examples to bring about positive change.

There is no shortage of horror stories in the development of AI, with algorithms that have been trained to reproduce the worst elements of society. There are many challenges that data scientists face in their work, from the gap between expectations and reality to lack of a framework for development opportunities, but among the reasons for quitting an otherwise well-paid job, ethical unease is always not far from the surface.

One major problem we’re all facing this year is food security. The pandemic, climate change and international unrest have combined to raise food prices globally. Author Afua Bruce cites the example of her local food bank, Rescuing Leftover Cuisine, which was established initially to take left over food to those who need it. The initial iteration of this non-profit charitable service was human based, with a network of volunteers contacting each other when they received a message that there was food to be collected and re-distributed. By automating that human process more efficiently through data solutions, they were able to reduce overheads. The key, according to Bruce, is to incorporate community feedback when creating a purpose built platform like the one used by Rescuing Leftover Cuisine. The charity was able to scale, and now services those in food poverty in eight cities around the United States.

The key takeaway from this book is that talking to community matters. Changing how we fund, create, develop and use technology is not easy. The authors do not believe that technology can produce a more equitable world, but with more technology deployed for good, that may become a compounding result. Rather than changing others around us, the process begins with looking at opportunities ourselves to evolve and challenge the values we hold. By focusing on transparency and accountability, the authors offer a model of AI that builds trust in communities and supports organizations to extend their mission in society through technology. A focus on the problem, not the tool, allows people to build better solutions, whatever field they are applying the technology to.

The best way to predict what the future will look like is to invent it and start building it now. This book will help you know where to start.

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Datacamp - Learning Tracks

All IoA members can use the installation-free Data Camp environments to build, practice and test your skills in Data Camp. We have two custom built tracks to allow you to ensure your training is on course to fulfil your career goals. We’ve recommended two tracks of knowledge and analytics study aligned to all of the 7 first years in the Data Competency Framework.

Which Track is for me?

Business analyst with R: This track will take you through spreadsheet skills and BI tools in the early years, and build up your coding skills to use R environments in the later years with more challenging data projects.

Python analyst: This track goes straight into Python coding and will take you all the way to working with unstructured data and deep learning techniques.

Look for the track name and year when you search for a course.

With our custom tracks, we’ve selected the skills that we know employers are looking for but remember that you can also take any of the 300 courses and assessments and projects any time you want and add that to your CPD records, too. You can find a post discussing the aims and structure of the tracks here


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