WEBVTT

1
00:00:00.160 --> 00:00:04.280
Wendy, Kate, hi. Kate,
urban areas use more energy.

2
00:00:04.670 --> 00:00:06.600
They produce more emissions.

3
00:00:06.600 --> 00:00:11.240
So what can the private sector
do in helping with this?

4
00:00:11.850 --> 00:00:12.640
So at Google,

5
00:00:12.640 --> 00:00:17.120
one of the big focus areas for us is how
do we bring our technology to partners

6
00:00:17.120 --> 00:00:21.400
in ways that can enable them to
understand their carbon emissions and set

7
00:00:21.400 --> 00:00:22.400
climate action targets.

8
00:00:22.400 --> 00:00:26.520
And cities have been a really great
area of focus for us. As you're noting,

9
00:00:26.520 --> 00:00:29.480
cities represent about
70% of global emissions.

10
00:00:29.810 --> 00:00:33.440
So several years ago we teamed up with
the Global Covenant of Mayors to build

11
00:00:33.440 --> 00:00:35.960
this tool called the
Environmental Insights Explorer.

12
00:00:36.340 --> 00:00:40.400
And it offers cities insights around
the carbon footprint of their buildings,

13
00:00:40.400 --> 00:00:43.680
their transportation, the solar
potential of their rooftops.

14
00:00:43.860 --> 00:00:45.640
And then in partnership with cities,

15
00:00:45.640 --> 00:00:48.000
they've been coming to us
asking us for new insights.

16
00:00:48.000 --> 00:00:52.240
Things like where should they be planting
trees to work on urban heat islands

17
00:00:52.240 --> 00:00:54.920
and improve air quality,
and also air quality data.

18
00:00:54.920 --> 00:00:57.400
How do we get more hyper local
information on air quality?

19
00:00:57.730 --> 00:01:01.040
So this is now available in
42,000 cities around the world,

20
00:01:01.260 --> 00:01:05.040
and we're seeing it really beginning to
have impact. So in the city of San Jose,

21
00:01:05.110 --> 00:01:07.160
they wanted to set an
ambitious solar target.

22
00:01:07.160 --> 00:01:10.760
They used this tool and they felt
confident setting a gigawatt solar target.

23
00:01:10.760 --> 00:01:12.760
And that's exactly the kind
of impact we wanna see.

24
00:01:12.800 --> 00:01:13.600
Wendy,

25
00:01:13.600 --> 00:01:18.160
talk to me about how technology can
contribute to mitigation and adaptation

26
00:01:18.160 --> 00:01:18.993
solutions.

27
00:01:19.210 --> 00:01:23.920
So technology is fundamentally a
critical enabler to actually making

28
00:01:24.200 --> 00:01:25.280
progress on any of this.

29
00:01:25.620 --> 00:01:30.240
One of the examples we're working
with many clients is using AI to help

30
00:01:30.240 --> 00:01:34.120
understand how to be much more
efficient in everything they're doing,

31
00:01:34.350 --> 00:01:38.600
less electricity, less materials.
And then on the adaptation front,

32
00:01:38.600 --> 00:01:42.280
technology enables you
to see so much more.

33
00:01:42.280 --> 00:01:46.000
The geospatial analysis that
we can do at massive scale,

34
00:01:46.000 --> 00:01:50.200
but at a level of detail allows the
kind of planning that we need to do for

35
00:01:50.200 --> 00:01:54.320
adaptation. So technology is fundamental
to making progress on both of those.

36
00:01:54.590 --> 00:01:57.120
Okay. What are some of the solutions
that Google is working on here,

37
00:01:57.170 --> 00:01:57.990
if you can tell me?

38
00:01:57.990 --> 00:02:01.720
Absolutely. So through
our Google Cloud team,

39
00:02:01.810 --> 00:02:04.080
we work with a lot of businesses as well.

40
00:02:04.180 --> 00:02:07.560
And it's all around this theme that I
think we're talking about a lot this week

41
00:02:07.560 --> 00:02:11.960
at COP- ambitions to action. Companies
have set bold climate action targets.

42
00:02:12.200 --> 00:02:14.640
We've set a net zero
target by 2030 for Google.

43
00:02:14.790 --> 00:02:16.480
Many other companies
have done this as well,

44
00:02:16.480 --> 00:02:18.520
and now they need help
achieving that target.

45
00:02:18.930 --> 00:02:20.920
So we are bringing our
technology to the table.

46
00:02:20.920 --> 00:02:25.800
We've worked with companies like UPS
to help them to optimize their routes.

47
00:02:25.800 --> 00:02:28.240
We're seeing major
efficiency opportunities,

48
00:02:28.240 --> 00:02:31.800
10 million gallons of fuel saved
through doing that optimization.

49
00:02:32.440 --> 00:02:36.520
Or companies like Unilever have net zero
targets and zero deforestation targets.

50
00:02:36.520 --> 00:02:37.560
And they came to us and said,

51
00:02:37.560 --> 00:02:41.400
we're having a really hard time getting
visibility upstream in our palm supply

52
00:02:41.400 --> 00:02:45.320
chain. So we brought to the table Google
Earth engine, you mentioned geospatial.

53
00:02:45.450 --> 00:02:50.400
An incredible geospatial tool enables
us to go deep on insights into

54
00:02:50.400 --> 00:02:52.760
what's happening on the ground so
they can achieve their targets.

55
00:02:53.050 --> 00:02:56.640
Of course, climate disasters
differ across the globe.

56
00:02:56.640 --> 00:03:01.640
So how can technology help here in
mitigation and adaptation strategies?

57
00:03:02.410 --> 00:03:06.280
So of course we know we're already
facing impacts of climate change today.

58
00:03:06.500 --> 00:03:10.760
And so this is a place where we've
seen a really powerful use case for AI.

59
00:03:10.970 --> 00:03:14.720
We have a team here in the region based
in Israel, our Google research team,

60
00:03:14.820 --> 00:03:19.560
and they've been working on flood
alerts providing AI to enable

61
00:03:19.560 --> 00:03:23.920
much better forecasting of flooding
so that we can provide SOS alerts to

62
00:03:23.920 --> 00:03:27.400
individuals and also give
governments more early warning signs.

63
00:03:27.530 --> 00:03:31.800
So we started this work
in a few communities where
flooding is a major issue in

64
00:03:31.800 --> 00:03:35.120
India and Bangladesh, and then we've
been using a machine learning model,

65
00:03:35.120 --> 00:03:38.000
It's getting trained and now
we're able to expand much further.

66
00:03:38.160 --> 00:03:41.520
So we just announced last week, it's
now gone to 15 countries in Africa,

67
00:03:41.910 --> 00:03:44.560
also dealing with flooding
from Cameroon to South Africa.

68
00:03:45.280 --> 00:03:48.360
Wendy, to change it, you need
to be able to measure it.

69
00:03:48.360 --> 00:03:50.720
And that unfortunately is one
of the problems with companies.

70
00:03:50.720 --> 00:03:52.280
They have the goals,
they have the ambitions,

71
00:03:52.380 --> 00:03:55.200
but tracking emissions is
a very difficult process.

72
00:03:55.290 --> 00:04:00.120
So how can technology help here and
also more generally companies to achieve

73
00:04:00.120 --> 00:04:01.840
their climate target goals?

74
00:04:02.790 --> 00:04:07.480
Technology enables you to measure
things right now and understanding

75
00:04:07.480 --> 00:04:11.360
your baseline in the first place and
then understanding what actions you can

76
00:04:11.360 --> 00:04:14.640
take to actually change and improve
on that baseline become incredibly

77
00:04:14.640 --> 00:04:17.280
important. One of our tools, C02.AI,

78
00:04:17.290 --> 00:04:21.280
is doing that with clients in
understanding and measuring the baseline,

79
00:04:21.370 --> 00:04:24.240
finding actions, and then
enabling that progress.

80
00:04:24.240 --> 00:04:25.880
That becomes incredibly important.

81
00:04:26.100 --> 00:04:28.760
The other thing I would say to
what you were referencing, Kate,

82
00:04:28.760 --> 00:04:33.040
is technology provides so many
nudges for all of us all day.

83
00:04:33.040 --> 00:04:36.760
And when we think about the behavioral
side of what we all need to do

84
00:04:36.760 --> 00:04:37.680
differently on climate,

85
00:04:37.980 --> 00:04:42.520
the nudges that technology provide us
in the right direction on what we can do

86
00:04:42.770 --> 00:04:44.880
to support climate become very important.

87
00:04:45.310 --> 00:04:46.800
I just wanna come in on that.

88
00:04:46.800 --> 00:04:50.480
That's another pillar of our strategy -
how do we enable everyone to be a part

89
00:04:50.480 --> 00:04:51.070
of the solution?

90
00:04:51.070 --> 00:04:54.640
What we know through Google search trends
is that people's interest in things

91
00:04:54.640 --> 00:04:57.160
like buying an electric
vehicle, a heat pump,

92
00:04:57.160 --> 00:05:00.360
putting solar on their roof are
at an all-time high in 2022.

93
00:05:00.500 --> 00:05:05.120
And what we see from the science from
the recent IPCC AR6 report is that

94
00:05:05.120 --> 00:05:09.880
these individual actions can add up
to about a 5% impact on emissions.

95
00:05:09.970 --> 00:05:13.360
So this is where we think we have a
huge opportunity with our products like

96
00:05:13.360 --> 00:05:17.360
Google Maps, where now in the US and
Canada, 40 countries across Europe,

97
00:05:17.580 --> 00:05:21.200
the most fuel efficient route is
now the default in Google Maps.

98
00:05:21.200 --> 00:05:22.120
We call this eco routing,

99
00:05:22.370 --> 00:05:27.120
as long as it has a similar ETA and just
after a few months of having that in

100
00:05:27.120 --> 00:05:27.590
the market,

101
00:05:27.590 --> 00:05:30.960
it's over a hundred thousand cars
off the road equivalent in emissions

102
00:05:30.960 --> 00:05:31.793
reductions.

103
00:05:32.070 --> 00:05:33.760
Okay, Wendy, thank you so much.

104
00:05:33.800 --> 00:05:34.720
Thank you.