Unusual problems that can be solved with Data Science

By arvind |Email | Sep 18, 2018 | 9273 Views

We do live in the world where no of problems is endless, while some of them are a problem because of technology, others just happened with passing time. Humans have turned to technology more often than not to find the solutions of the existing problems of this world. Data Science is also a technology that companies and institute have turned in hope they could solve some problems. 
Here is a non-exhausting list of curious problems that could greatly benefit from data analysis. If you think you can't get a job as a data scientist, here's a way to find or create new jobs, broaden your horizons, and make Earth a better world not just for human beings, but for all living creatures. Even beyond Earth indeed. 

Here are a few unusual problems that can be solved with data science

1. Automated translation, including translating one programming language into another one (for instance, SQL to Python - the converse is not possible)
2. Spell checks, especially for people writing in multiple languages - lot's of progress to be made here, including automatically recognizing the language when you type, and stop trying to correct the same word every single time (some browsers have tried to change Ning to Nong hundreds of times, and I have no idea why after 50 failures they continue to try - I call this machine unlearning) 
3. Detection of earth-like planets - focus on planetary systems with many planets to increase odds of finding inhabitable planets, rather than stars and planets matching our Sun and Earth
4. Distinguishing between noise and signal on millions of NASA pictures or videos, to identify patterns
5. Automated piloting (drones, cars without pilots)
6. Customized, patient-specific medications and diets
7. Predicting and legally manipulating elections
8. Sport bets
9. Predicting oil demand, oil reserves, oil price, impact of coal usage
10. Predicting chances that a container in a port contains a nuclear bomb
11. Assessing the probability that a convict is really the culprit, especially when a chain of events resulted in a crime or accident (think about a civil airplane shot down by a missile)
12. Computing correct average time-to-crime statistics for an average gun (using censored models to compensate for the bias caused by new guns not having a criminal history attached to them)
13. Predicting iceberg paths: this occasionally requires icebergs to be towed to avoid collisions
14. Oil wells drilling optimization: how to dig as few test wells as possible to detect the entire area where oil can be found 
15. Predicting solar flares: timing, duration, intensity and localization
16. Predicting Earthquakes
17. Predicting very local weather (short-term) or global weather (long-term); reconstructing past weather (like 200 million years old)
18. Predicting weather on Mars to identify best time and spots for a landing
19. Predict riots based on tweets
20. Designing metrics to predict student success, or employee attrition
21. Predicting book sales, determining correct price, price elasticity and whether a specific book should be accepted or rejected by a publisher, based on projected ROI
22. Predicting volcano risk, to evacuate populations or cancel flights, while minimizing expenses caused by these decisions
23. Predicting 500-year floods, to build dams
24. Actuarial science: predict your death, and health expenditures, to compute your premiums (based on which population segment you belong to)
25. Predicting reproduction rate in animal populations
26. Predicting food reserves each year (fish, meat, crops including crop failures caused by diseases or other problems). Same with electricity and water consumption, as well as rare metals or elements those are critical to build computers and other modern products.
27. Predicting longevity of a product, or a customer
28. Asteroid risks
29. Predicting duration, extent and severity of draught or fires
30. Predicting racial and religious mix in a population, detecting change point (e.g. when more people speak Spanish than English, in California) to adapt policies accordingly

While these are some problems that could be solved using AI, these are not all the problems that can be solved using Data Science. So problems are already being solved will others are being worked on. 

Source: HOB