Page 14 - Summer 2024

VILNIUS UNIVERSITY
USES AI KNOWLEDGE
TWINS TO TEACH LAW
The University of Vilnius’ Law Faculty has
created an innovative educational tool using
AI. In the Spring semester of 2024 two faculty
members, Dr. Paul Jurcys and PhD candidate
Goda Strikaite-Latusinskaya, applied next-
generation tools by integrating their AI
knowledge twins into the curriculum.
An AI knowledge twin is a digital avatar that
contains the knowledge and expertise of its
‘owner’ and its knowledge base includes the
scientific publications, teaching material and
additional information of this owner. The AI
Knowledge Avatars ‘Paul AI’ and ‘Goda AI’ have
been used to teach the course ‘Data Protection
Law: A Human-Centric Approach’.
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Scholars have discovered that ‘Paul AI’ and
‘Goda AI’ have offered a new way to engage
with their professors and access information by
asking questions and discussing accumulated
knowledge.
The intensive course has been designed to
integrate theoretical knowledge with the
practical application of knowledge and the use
of AI tools. The first four lectures on ‘Data Privacy
Law’ focused on the principles of a new, human-
centric approach to personal data and aimed
to highlight new data usage models that are
intended to create new ways of using personal
data for the benefit of individuals.
As part of their preparation for the lectures
students completed specific practical tasks
using ‘Paul AI’ and ‘Goda AI’ and other AI tools.
Subsequent lectures divided the students into
groups tasked with selecting topics related to
data usage, identifying specific problems and
preparing presentations to solve these problems.
Students were encouraged to use any AI tools of
their choice.
For the exam input was sought from educators
and EduTech experts from the USA, Japan,
Denmark and the Netherlands.
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FLOWER-COUNTING AI HELPS
FRUIT FARMERS PREDICT CROPS
A new AI system that counts flowers on fruit
trees is helping farmers to predict harvest sizes
months in advance, making crop yields more
efficient, sustainable and profitable.
Developed by researchers in Scotland, Chile
and Spain, the system uses images taken with a
standard smartphone to accurately estimate the
number of flowers on a fruit tree by recognising
patterns and features such as the edges and
shapes of petals even when they overlap or are
partially obscured.
Tests on peach orchards in Catalonia in Spain
showed a 90 per cent accuracy in AI predicted
flower counts, representing a significant
improvement on the manual methods currently
used by farmers, such as counting by eye or
taking area samples, which can have error rates
of between 30 and 50 per cent.
These more precise yield forecasts are
envisaged to be able to help fruit growers
optimise water usage, allocate human and
economic resources more efficiently, and better
plan harvesting and distribution logistics.
Researchers at the National Robotarium in
Edinburgh will validate the AI predictions against
the region’s actual peach harvest in September
and if proven to be effective will be considered
for adoption with other crops such as apples,
pears and cherries.
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Fernando Anat Cheein, Associate Professor
of Robotics and Autonomous Systems at the
National Robotarium, states:
“In countries all across the world, farmers often
rely on manual methods to estimate their yields,
which can have a significant error margin. By
leveraging the power of AI and the convenience
of off-the-shelf technology like smartphones, our
approach seamlessly integrates with traditional
farming practices, making it easier for growers to
embrace and benefit from innovative solutions
without overhauling their existing methods.
Throughout the project, we worked closely with
peach farmers in Spain to understand their
challenges and ensure the system met their
requirements. The farmers appreciated the
simplicity and accuracy of the flower counting AI,
noting its potential to help make more informed
decisions about crop management, such as
targeted pruning and herbicide application. By
focusing their efforts on areas of the farm that
are expected to yield the most fruit, farmers can
optimise resources, reduce their environmental
footprint, and maximise both the quantity and
quality of their harvest.
While our research has focused on peaches,
the principles behind this technology could be
applied to a wide range of fruit crops worldwide,
including those grown in the UK”.
Reference: Tyler, N., New Electronics, 18th. June
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