Our Vision

Apply Magic Sauce is a non-profit academic research project coordinated by the University of Cambridge Psychometrics Centre. The demos and platforms available here are a modest attempt to reverse the trend in Big Data and empower citizens to not only retain control of their data but also derive meaningful insight from it.

We build analytics tools that you can use on your own data to see how others see you, and we collect anonymous opt-in datasets to advance scientific enquiry into online behavior, digital footprint analysis and artificial intelligence. We believe in the power of academia for real-world impact and care not about identifying you personally, but providing you with tools to individualise your own experience.

Why? Because your online experiences are constantly tweaked and tailored based on an algorithm’s best guess at what you might want in a given moment. Most data-driven tools try to build up a picture of you by collecting as much of your past behaviour as possible – scraping, tracking or buying whatever information they can get. Instead, we feel there should be a greater focus on the psychological traits and emotions that drive behaviour, not merely the fact you have clicked or Liked something. Apply Magic Sauce allows you to understand your own digital footprint so you are better equipped to negotiate with anyone who tries to collect or process it in future.

Ethics

We encourage companies and academics to adhere to the following ethical principles, in addition to the applicable legal restrictions. These are based on our experience, and supported by a Psychometrics Centre survey of over 34,000 participants worldwide regarding how they would like their Big Data to be used:

Control

No user should have predictions made about them without their prior informed consent

Transparency

The results of any predictions made about a user should be clearly shared with them

Benefit

Predictions should be used to improve user experience and provide a worthwhile benefit

Relevance

It should be clear why the data requested from the user is relevant to the prediction being made

How It Could Look

Apply Magic Sauce API enables conversations between citizens and data processors about how predictive technologies ought to be used. This could help algorithms explain themselves and learn from their mistakes, just like humans, while building trust in the system.

Choose a character to discover how their personality might affect their online experience, or click Predict My Profile to see how others see you

Openness
90%
Openness to Experience is the extent to which people prefer novelty over convention; it distinguishes imaginative, creative people from down-to-earth, conventional ones.
Conscientiousness
20%
Conscientiousness is the extent to which people prefer an organized or a flexible approach in life, and is concerned with the way in which we control, regulate, and direct our impulses.
Extraversion
40%
Extraversion is the extent to which people enjoy company, and seek excitement and stimulation. It is marked by pronounced engagement with the external world, versus being comfortable with one’s own company.
Agreeableness
50%
Agreeableness reflects individual differences concerning cooperation and social harmony. It refers to the way people express their opinions and manage relationships.
Neuroticism
60%
Neuroticism refers to the tendency to experience negative emotions, and concerns the way people cope with and respond to life’s demands.

Share with us your digital footprint

And we will return a psycho-demographic profile

Our models are based exclusively on opt-in data from millions of research participants, comprising both social media profiles and matching scores on psychometric tests. This gives us the unique ability to demonstrate how our predictions compare to validated tools that have been in use by psychometricians for decades. We publish our results in scientific journals and stimulate open debate about the future of predictive technologies using digital footprint analysis.

We put people before predictions

Making artificial intelligence more interpretable

Machine-learning algorithms can be difficult to understand, let alone implement in a product. Without psychological sensitivity, these algorithms are at risk of perpetuating historical prejudice, being overly domain-specific or prescribing norms that can feel impersonal. We know that patterns of human activity are usually not random, so we always think beyond the mere clicks or Likes in your digital footprint and try to reveal the subtle attributes that really drive your behaviour.

Add psychological data points to any sample

Trait predictions turn gaps in your knowledge into actionable insights

Connected devices are recording everything we do and want - our pulse, our purchases, our personality, it’s all part of the internet. The websites we visit and the brands we interact with can certainly be very informative, but these are noisy snippets of behaviour, not the whole picture. Our psychometric techniques can identify and fill the gaps in your knowledge about yourself or your research participants. We pave the way for collaborative tools through which citizens can better extract informational or commercial value from their own data.

Developed at the University of Cambridge Psychometrics Centre

Apply Magic Sauce is the product of a unique dataset, a multi-disciplinary team and a supportive academic environment. It was assembled by researchers at the University of Cambridge Psychometrics Centre and builds upon a 30-year legacy of leadership in advanced psychological measurement and computational behavioural science.