How the Internet Can Know What You Want Before You Do: Web-Based Machine Learning Applications for Wildlife Management

Abstract

Web-based decision support tools that use machine learning algorithms are becoming increasingly important in our technology driven society. This is because fast access to the most recent or best information allows managers to make efficient, fact-driven decisions under certain circumstances. Web-based tools have the potential to allow managers to engage more easily in adaptive management, where mitigation techniques can be implemented in a near real-time basis. This is common practice in the business community, but has yet to permeate the wildlife management field. The success of data mining and machine learning for decision support leads us to conclude that web-based tools that take advantage of these algorithms would greatly improve management strategies globally. Furthermore, as many of the skills to build these applications are often lacking in a single individual, they encourage the creation of creative teams consisting of scientists, designers and computer experts, making them inter-disciplinary projects, In this chapter, I explore web-based machine learning applications for decision support and their potential importance for wildlife management. I first go over the importance of web-based tools and how they offer a platform for transparent and public science, and then explore this using a few case examples. I then go over several frameworks available for budding machine learning enthusiasts and how they can go from database to data application in a short period of time.