PySpark 3.4.0 cannot convert timestamp-typed objects to pandas with pandas 2.0

In [1]: from pyspark.sql import SparkSession

In [2]: session = SparkSession.builder.appName("test").getOrCreate()
23/04/19 09:21:42 WARN Utils: Your hostname, albatross resolves to a loopback address: 127.0.0.2; using 192.168.1.170 instead (on interface enp5s0)
23/04/19 09:21:42 WARN Utils: Set SPARK_LOCAL_IP if you need to bind to another address
Setting default log level to "WARN".
To adjust logging level use sc.setLogLevel(newLevel). For SparkR, use setLogLevel(newLevel).
23/04/19 09:21:42 WARN NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable

In [3]: session.sql("select now()").toPandas()

...
TypeError: Casting to unit-less dtype 'datetime64' is not supported. Pass e.g. 'datetime64[ns]' instead.