A Human Machine Hybrid Approach for Systematic Reviews and Maps in International Development and Social Impact Sectors

Murat Sartas,Sarah Cummings,Alessandra Garbero,Akmal Akramkhanov

doi:10.3390/f12081027

Murat Sartas, Sarah Cummings + Show 2 more

Open Access

https://doi.org/10.3390/f12081027

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Abstract

The international development and social impact evidence community is divided about the use of machine-centered approaches in carrying out systematic reviews and maps. While some researchers argue that machine-centered approaches such as machine learning, artificial intelligence, text mining, automated semantic analysis, and translation bots are superior to human-centered ones, others claim the opposite. We argue that a hybrid approach combining machine and human-centered elements can have higher effectiveness, efficiency, and societal relevance than either approach can achieve alone. We present how combining lexical databases with dictionaries from crowdsourced literature, using full texts instead of titles, abstracts, and keywords. Using metadata sets can significantly improve the current practices of systematic reviews and maps. Since the use of machine-centered approaches in forestry and forestry-related reviews and maps are rare, the gains in effectiveness, efficiency, and relevance can be very high for the evidence base in forestry. We also argue that the benefits from our hybrid approach will increase in time as digital literacy and better ontologies improve globally.

Highlights

Information and communication technologies have made significant advances in the last decades and disrupted science and other knowledge sectors
We think our hybrid approach for conducting systematic reviews and maps can address most concerns about evidence management and improve the efficiency, effectiveness, and societal relevance of systematic reviews and maps
We propose using the hybrid approach, especially in the evidence sector in international development, social impact, and broader forest use, as well as management sectors that shaped our perspective leading to the design and development of the hybrid approach

Summary

Introduction

Information and communication technologies have made significant advances in the last decades and disrupted science and other knowledge sectors. The changes in systematic review methodologies and tools in international development and social impact sectors have been much slower. There are many missed opportunities to increase the effectiveness, efficiency, and societal relevance of systematic reviews and maps in international development and social impact sectors. One of the root causes of the slow change in the evidence sector in general and systematic reviews, in particular, is the polarization of the opinion about the role of machine-centered systems. We think our hybrid approach for conducting systematic reviews and maps can address most concerns about evidence management and improve the efficiency, effectiveness, and societal relevance of systematic reviews and maps. We think that broader forest use and management sectors, including land management, are among the fields that can benefit from the approach for addressing the key challenges in contemporary forestry

Current Challenges in Systematic Review and Map Sector

A Hybrid Approach to Address the Challenges

Comparison

Using Metadata Sets for Mapping and Synthesizing the Evidence