The herbarium of Washington, D.C.'s Natural History Museum teems with pressed specimens of thousands of distinct plants. (National Museum of Natural History)

How are AI and Machine Learning currently being implemented in museums?

My first research question is: How are AI and Machine Learning currently being implemented in museums?

New technologies like artificial intelligence (AI) and machine learning are being implemented in several different ways by museums. Typically, these efforts can be divided into two categories with each its own use case.

The first way new technologies are being used, is by implementing machine learning to analyse museum data. Museums have typically collected vasts amounts of data over the years. Manually analysing samples and records would take trained professionals many years to complete, making it a tedious, time-intensive and very expensive task. By using machine learning algorithms, large amounts of data can be analysed quickly and patterns can easily be detected. (Smith, 2017)

A great example of this is the National Museum of Natural History in Washington D.C. Their botanical collection, consisting of items like pressed flowers and grasses, contains no less than five million specimens. By installing a camera and conveyor belt construction, they are able to digitize 750,000 specimens each year. Neural networks are then able to categorise and distinguish the samples with an accuracy of over 90%. After this process is done, the curators will use all this data to look for new patterns on a global scale, something that was unimaginable just a couple of years ago. (Smith, 2017)(Ciecko, 2018)

The second way new technologies are being implemented by museums, is by using artificial intelligence to aid visitors. This is usually done by developing chatbots, most of which are Facebook chatbots. (Ashri, 2017)(Berger, 2017)

However, chatbots in museums are nothing new. In 2004, Max the conversational agent was created, becoming one of the more famous bots to guide visitors in museums. Since then, it’s become easier and cheaper to create chatbots, which is why they’ve been making a comeback. (Kopp, Gesellensetter, Kramer, Wachsmuth, 2004)

The Historic Voicebot falls into this last category of artificial intelligence that aids museum visitors. In the chapter “Competition Analysis”, I’ve taken a closer look at some of the chatbots being used in museums and the research that’s been done about them.

To summarise, new technologies like AI and Machine Learning are currently being implemented by museums to either analyse the vast amounts of data they have, or to aid the visitors.

27/11/2018

Sources:

ASHRI (R.), How museums are using chatbots – 5 real world examples, Deeson, 2017, https://www.deeson.co.uk/blog/how-museums-are-using-chatbots-5-real-world-examples Date of reference: 11th of October 2018.

BERGER (B.), AI-enabled technologies could help museums survive the digital age, venturebeat, 2017, https://venturebeat.com/2017/11/06/ai-enabled-technologies-could-help-museums-survive-the-digital-age/ Date of reference: 18th of November 2018.

CIECKO (B.), Exploring Artificial Intelligence in museums, 2016, https://cuseum.com/blog/exploring-artificial-intelligence-in-museums Date of reference: 18th of November 2018.

KOPP (S.), GESELLENSETTER (L.), KRAMER (N.),WACHSMUTH (I.), A Conversational Agent as Museum Guide – Design and Evaluation of a Real-World Application, 2004, https://www.techfak.uni-bielefeld.de/~skopp/download/museumguide.pdf Date of reference: 12th of October 2018.

SMITH (R.), How Artificial Intelligence Could Revolutionize Archival Museum Research,  Smithsonian, 2017, https://www.smithsonianmag.com/smithsonian-institution/how-artificial-intelligence-could-revolutionize-museum-research-180967065/  Date of reference: 18th of November 2018.

Image source:
SMITH (R.), How Artificial Intelligence Could Revolutionize Archival Museum Research,  Smithsonian, 2017, https://www.smithsonianmag.com/smithsonian-institution/how-artificial-intelligence-could-revolutionize-museum-research-180967065/  Date of reference: 18th of November 2018.